{"id":10626,"date":"2021-03-07T13:00:00","date_gmt":"2021-03-07T09:30:00","guid":{"rendered":"https:\/\/shahaab-co.com\/mag\/?p=10626"},"modified":"2024-11-29T18:37:09","modified_gmt":"2024-11-29T15:07:09","slug":"deep-neural-network-python-keras","status":"publish","type":"post","link":"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/","title":{"rendered":"\u067e\u0631\u0648\u0698\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 Keras \u0628\u0647 \u0635\u0648\u0631\u062a \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645"},"content":{"rendered":"<p style=\"text-align: justify;\"><a href=\"https:\/\/keras.io\/\" target=\"_blank\" rel=\"noopener noreferrer\">Keras<\/a> \u06cc\u06a9 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0646\u0628\u0639 \u0628\u0627\u0632 \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0648 \u0628\u0627 \u06a9\u0627\u0631\u0628\u0631\u062f \u0622\u0633\u0627\u0646 \u0628\u0631\u0627\u06cc \u062a\u0648\u0633\u0639\u0647 \u0648 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u06a9\u0631\u0627\u0633\u060c \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647\u200c\u0647\u0627\u06cc \u0645\u062d\u0627\u0633\u0628\u0627\u062a\u06cc \u0639\u062f\u062f\u06cc <a href=\"https:\/\/github.com\/Theano\/Theano\" target=\"_blank\" rel=\"noopener noreferrer\">Theano<\/a> \u0648 <a href=\"https:\/\/www.tensorflow.org\/\" target=\"_blank\" rel=\"noopener noreferrer\">TensorFlow<\/a> \u0631\u0627 \u06a9\u0627\u0631\u0622\u0645\u062f \u06a9\u0631\u062f\u0647 \u0648 \u0628\u0647 \u0634\u0645\u0627 \u0627\u06cc\u0646 \u00a0\u0627\u0645\u06a9\u0627\u0646 \u0631\u0627 \u0645\u06cc\u200c\u062f\u0647\u062f \u06a9\u0647 \u0641\u0642\u0637 \u062f\u0631 \u0686\u0646\u062f \u062e\u0637 \u06a9\u062f\u060c \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u0648 \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0631 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u060c \u0634\u0645\u0627 \u062e\u0648\u0627\u0647\u06cc\u062f \u0641\u0647\u0645\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0627\u0648\u0644\u06cc\u0646 \u0645\u062f\u0644 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u062e\u0648\u062f \u0631\u0627 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 Keras \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u06cc\u0627\u06cc\u06cc\u062f \u0634\u0631\u0648\u0639 \u06a9\u0646\u06cc\u0645.<\/p>\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_76 counter-hierarchy ez-toc-counter-rtl ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u0622\u0646\u0686\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628 \u062e\u0648\u0627\u0647\u06cc\u0645 \u062e\u0648\u0627\u0646\u062f :<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #0044bf;color:#0044bf\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 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ez-toc-heading-2\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%D9%86%DB%8C%D8%A7%D8%B2%D9%85%D9%86%D8%AF%DB%8C_%D9%87%D8%A7%DB%8C_%D8%A7%DB%8C%D9%86_%D8%A2%D9%85%D9%88%D8%B2%D8%B4_%DA%A9%D8%B1%D8%A7%D8%B3\" >\u0646\u06cc\u0627\u0632\u0645\u0646\u062f\u06cc \u0647\u0627\u06cc \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u06a9\u0631\u0627\u0633 :<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B1-_%D8%A8%D8%A7%D8%B1%DA%AF%D8%B0%D8%A7%D8%B1%DB%8C_%D8%AF%D8%A7%D8%AF%D9%87_%D9%87%D8%A7\" >\u06f1- \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B2-_%D9%85%D8%AF%D9%84_Keras_%D8%B1%D8%A7_%D8%AA%D8%B9%D8%B1%DB%8C%D9%81_%DA%A9%D9%86%DB%8C%D8%AF\" >\u06f2- \u0645\u062f\u0644 Keras \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0646\u06cc\u062f<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B3-_%D9%85%D8%AF%D9%84_Keras_%D8%B1%D8%A7_%DA%A9%D8%A7%D9%85%D9%BE%D8%A7%DB%8C%D9%84_%DA%A9%D9%86%DB%8C%D8%AF\" >\u06f3- \u0645\u062f\u0644 Keras \u0631\u0627 \u06a9\u0627\u0645\u067e\u0627\u06cc\u0644 \u06a9\u0646\u06cc\u062f<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B4-_Fit_%DA%A9%D8%B1%D8%AF%D9%86_%D8%A8%D8%A7_%D9%85%D8%AF%D9%84_Keras\" >\u06f4- Fit \u06a9\u0631\u062f\u0646 \u0628\u0627 \u0645\u062f\u0644 Keras<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B5-_%D9%85%D8%AF%D9%84_Keras_%D8%B1%D8%A7_%D8%A7%D8%B1%D8%B2%DB%8C%D8%A7%D8%A8%DB%8C_%DA%A9%D9%86%DB%8C%D8%AF\" >\u06f5- \u0645\u062f\u0644 Keras \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u06cc\u062f<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B6-_%D9%87%D9%85%D9%87_%D8%B1%D8%A7_%D8%A8%D8%A7_%D9%87%D9%85_%D8%AA%D8%AC%D9%85%DB%8C%D8%B9_%DA%A9%D9%86%DB%8C%D8%AF\" >\u06f6- \u0647\u0645\u0647 \u0631\u0627 \u0628\u0627 \u0647\u0645 \u062a\u062c\u0645\u06cc\u0639 \u06a9\u0646\u06cc\u062f<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%DB%B7-_%D9%BE%DB%8C%D8%B4_%D8%A8%DB%8C%D9%86%DB%8C_%D8%B1%D8%A7_%D8%A7%D9%86%D8%AC%D8%A7%D9%85_%D8%AF%D9%87%DB%8C%D8%AF\" >\u06f7- \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u062f<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%D8%AE%D9%84%D8%A7%D8%B5%D9%87_%D8%A2%D9%85%D9%88%D8%B2%D8%B4_%DA%A9%D8%B1%D8%A7%D8%B3\" >\u062e\u0644\u0627\u0635\u0647 \u0622\u0645\u0648\u0632\u0634 \u06a9\u0631\u0627\u0633<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-neural-network-python-keras\/#%D9%85%D9%88%D8%A7%D8%B1%D8%AF_%D8%A7%D8%B6%D8%A7%D9%81%D9%87_%D8%A2%D9%85%D9%88%D8%B2%D8%B4_Keras\" >\u0645\u0648\u0627\u0631\u062f \u0627\u0636\u0627\u0641\u0647 \u0622\u0645\u0648\u0632\u0634 Keras<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%D8%A2%D9%85%D9%88%D8%B2%D8%B4_Keras\"><\/span><strong>\u0622\u0645\u0648\u0632\u0634 Keras<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u06a9\u062f \u0632\u06cc\u0627\u062f\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0646\u06cc\u0633\u062a \u060c \u0627\u0645\u0627 \u0645\u0627 \u06a9\u0645\u06cc \u062a\u0648\u0636\u06cc\u062d \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u0627\u062f \u062a\u0627 \u062f\u0631 \u0622\u06cc\u0646\u062f\u0647 \u0628\u062f\u0627\u0646\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0633\u0627\u0632\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0631\u0627\u062d\u0644\u06cc \u06a9\u0647 \u0642\u0631\u0627\u0631 \u0627\u0633\u062a \u062f\u0631 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0637\u06cc \u06a9\u0646\u06cc\u062f \u0628\u0647 \u0634\u0631\u062d \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n\n\n<div class=\"wp-block-rank-math-toc-block\"><ul><li><a href=\"#h-1\" >\u06f1- \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627<\/a><\/li><li><a href=\"#h-2-keras\" >\u06f2- \u0645\u062f\u0644 Keras \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0646\u06cc\u062f<\/a><\/li><li><a href=\"#h-3-keras\" >\u06f3- \u0645\u062f\u0644 Keras \u0631\u0627 \u06a9\u0627\u0645\u067e\u0627\u06cc\u0644 \u06a9\u0646\u06cc\u062f<\/a><\/li><li><a href=\"#h-4-fit-keras\" >\u06f4- Fit \u06a9\u0631\u062f\u0646 \u0628\u0627 \u0645\u062f\u0644 Keras<\/a><\/li><li><a href=\"#h-5-keras\" >5- \u0645\u062f\u0644 Keras \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u06cc\u062f<\/a><\/li><li><a href=\"#h-6\" >\u06f6- \u0647\u0645\u0647 \u0631\u0627 \u0628\u0627 \u0647\u0645 \u062a\u062c\u0645\u06cc\u0639 \u06a9\u0646\u06cc\u062f<\/a><\/li><li><a href=\"#h-7\" >\u06f7- \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u062f<\/a><\/li><\/nav><\/ul><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%D9%86%DB%8C%D8%A7%D8%B2%D9%85%D9%86%D8%AF%DB%8C_%D9%87%D8%A7%DB%8C_%D8%A7%DB%8C%D9%86_%D8%A2%D9%85%D9%88%D8%B2%D8%B4_%DA%A9%D8%B1%D8%A7%D8%B3\"><\/span><strong>\u0646\u06cc\u0627\u0632\u0645\u0646\u062f\u06cc \u0647\u0627\u06cc \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u06a9\u0631\u0627\u0633 :<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<ul>\n<li style=\"text-align: justify;\">Python 2 \u06cc\u0627 \u06f3 \u0631\u0627 \u0646\u0635\u0628 \u0648 \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u06a9\u0631\u062f\u0647 \u0628\u0627\u0634\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\">SciPy ( \u0628\u0647 \u0647\u0645\u0631\u0627\u0647 NumPy) \u0631\u0627 \u0646\u0635\u0628 \u0648 \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u06a9\u0631\u062f\u0647 \u0628\u0627\u0634\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\">Keras \u0648 \u06cc\u06a9 backend (Theano \u06cc\u0627 TensorFlow) \u0631\u0627 \u0646\u0635\u0628 \u0648 \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u06a9\u0631\u062f\u0647 \u0628\u0627\u0634\u06cc\u062f.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">\u0627\u06af\u0631 \u062f\u0631 \u0632\u0645\u06cc\u0646\u0647 \u0645\u062d\u06cc\u0637 \u0628\u0647 \u06a9\u0645\u06a9 \u0646\u06cc\u0627\u0632 \u062f\u0627\u0631\u06cc\u062f \u060c \u0628\u0647 \u0622\u0645\u0648\u0632\u0634 \u0632\u06cc\u0631 \u0645\u0631\u0627\u062c\u0639\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<p style=\"text-align: justify;\"><u><a href=\"http:\/\/machinelearningmastery.com\/setup-python-environment-machine-learning-deep-learning-anaconda\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0646\u062d\u0648\u0647 \u062a\u0646\u0638\u06cc\u0645 \u0645\u062d\u06cc\u0637 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642<\/a><\/u><\/p>\n<p style=\"text-align: justify;\">\u06cc\u06a9 \u0641\u0627\u06cc\u0644 \u062c\u062f\u06cc\u062f \u0628\u0647 \u0646\u0627\u0645 keras_first_network.py \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f \u0648 \u06a9\u062f \u0631\u0627 \u062f\u0631 \u0622\u0646 \u062a\u0627\u06cc\u067e \u06cc\u0627 \u06a9\u067e\u06cc \u06a9\u0646\u06cc\u062f.<\/p>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-1\"><span class=\"ez-toc-section\" id=\"%DB%B1-_%D8%A8%D8%A7%D8%B1%DA%AF%D8%B0%D8%A7%D8%B1%DB%8C_%D8%AF%D8%A7%D8%AF%D9%87_%D9%87%D8%A7\"><\/span><strong>\u06f1- \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0627\u0648\u0644\u06cc\u0646 \u0642\u062f\u0645 \u062a\u0639\u0631\u06cc\u0641 \u062a\u0648\u0627\u0628\u0639 \u0648 \u06a9\u0644\u0627\u0633 \u0647\u0627\u06cc\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0642\u0635\u062f \u062f\u0627\u0631\u06cc\u0645 \u062f\u0631 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0628\u0631\u0627\u06cc \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062e\u0648\u062f \u0627\u0632 <a href=\"https:\/\/www.numpy.org\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 NumPy<\/a> \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u0648 \u0628\u0631\u0627\u06cc \u062a\u0639\u0631\u06cc\u0641 \u0645\u062f\u0644 \u062e\u0648\u062f \u0627\u0632 \u062f\u0648 \u06a9\u0644\u0627\u0633 \u0627\u0632 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Keras \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f.<\/p>\n<p style=\"text-align: justify;\">\u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u062f\u0631 \u0632\u06cc\u0631 \u0630\u06a9\u0631 \u0634\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># first neural network with keras tutorial\nfrom numpy import loadtxt\nfrom keras.models import Sequential\nfrom keras.layers import Dense\n...<\/pre>\n<p style=\"text-align: justify;\">\u0627\u06a9\u0646\u0648\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062e\u0648\u062f \u0631\u0627 \u0628\u0627\u0631\u06af\u06cc\u0631\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0631 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 Keras \u060c \u0645\u0627 \u0642\u0635\u062f \u062f\u0627\u0631\u06cc\u0645 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc Pima Indians \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062f\u06cc\u0627\u0628\u062a \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645. \u0627\u06cc\u0646 \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u0633\u062a\u0627\u0646\u062f\u0627\u0631\u062f \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0627\u0632 \u0645\u062e\u0632\u0646 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 UCI \u0627\u0633\u062a. \u0627\u06cc\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u0633\u0648\u0627\u0628\u0642 \u067e\u0632\u0634\u06a9\u06cc \u0628\u06cc\u0645\u0627\u0631\u0627\u0646 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0633\u0631\u062e\u067e\u0648\u0633\u062a\u0627\u0646 \u067e\u06cc\u0645\u0627 \u0648 \u0627\u06cc\u0646\u06a9\u0647 \u0622\u06cc\u0627 \u0622\u0646 \u0647\u0627 \u062f\u0631 \u0637\u06cc \u067e\u0646\u062c \u0633\u0627\u0644 \u0634\u0631\u0648\u0639 \u062f\u06cc\u0627\u0628\u062a \u062f\u0627\u0634\u062a\u0647 \u0627\u0646\u062f \u06cc\u0627 \u0646\u0647 \u060c \u062a\u0648\u0635\u06cc\u0641 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u0647 \u0647\u0645\u06cc\u0646 \u062a\u0631\u062a\u06cc\u0628 \u060c \u0627\u06cc\u0646 \u06cc\u06a9 \u0645\u0634\u06a9\u0644 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0628\u0627\u06cc\u0646\u0631\u06cc \u0627\u0633\u062a (\u0634\u0631\u0648\u0639 \u062f\u06cc\u0627\u0628\u062a \u06f1 \u06cc\u0627 \u0646\u0647 \u06f0). \u062a\u0645\u0627\u0645 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u06a9\u0647 \u0647\u0631 \u0628\u06cc\u0645\u0627\u0631 \u0631\u0627 \u062a\u0648\u0635\u06cc\u0641 \u0645\u06cc \u06a9\u0646\u0646\u062f \u060c \u0639\u062f\u062f\u06cc \u0647\u0633\u062a\u0646\u062f. \u0627\u06cc\u0646 \u0627\u0645\u0631 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0646 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0634\u0628\u06a9\u0647 \u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u06a9\u0647 \u0627\u0646\u062a\u0638\u0627\u0631 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0648\u0631\u0648\u062f\u06cc \u0648 \u062e\u0631\u0648\u062c\u06cc \u0639\u062f\u062f\u06cc \u0631\u0627 \u062f\u0627\u0631\u0646\u062f \u0648 \u0628\u0631\u0627\u06cc \u0627\u0648\u0644\u06cc\u0646 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0645\u0627 \u062f\u0631 \u06a9\u0631\u0627\u0633 \u0627\u06cc\u062f\u0647 \u0622\u0644 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0627\u0632 \u0622\u062f\u0631\u0633 \u0632\u06cc\u0631 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0627\u0646\u0644\u0648\u062f \u06a9\u0646\u06cc\u062f:<\/p>\n<p style=\"text-align: justify;\"><u><a href=\"https:\/\/raw.githubusercontent.com\/jbrownlee\/Datasets\/master\/pima-indians-diabetes.data.csv\" target=\"_blank\" rel=\"noopener\">\u067e\u0631\u0648\u0646\u062f\u0647 Dataset CSV (pima-indians-diabet.csv)<\/a><\/u><\/p>\n<p style=\"text-align: justify;\"><a href=\"https:\/\/raw.githubusercontent.com\/jbrownlee\/Datasets\/master\/pima-indians-diabetes.names\" target=\"_blank\" rel=\"noopener\">\u062c\u0632\u0626\u06cc\u0627\u062a \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/a><\/p>\n<p style=\"text-align: justify;\">\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0628\u0627\u0631\u06af\u06cc\u0631\u06cc \u06a9\u0631\u062f\u0647 \u0648 \u062f\u0631 \u0641\u0647\u0631\u0633\u062a \u0645\u062d\u0644\u06cc \u06a9\u0627\u0631 \u062e\u0648\u062f \u060c \u0647\u0645\u0627\u0646 \u0645\u06a9\u0627\u0646 \u0641\u0627\u06cc\u0644 \u067e\u0627\u06cc\u062a\u0648\u0646 \u060c \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0622\u0646 \u0631\u0627 \u0628\u0627 \u0646\u0627\u0645 \u067e\u0631\u0648\u0646\u062f\u0647 \u0630\u062e\u06cc\u0631\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">pima-indians-diabetes.csv<\/pre>\n<p style=\"text-align: justify;\">\u0628\u0647 \u062f\u0627\u062e\u0644 \u067e\u0631\u0648\u0646\u062f\u0647 \u0646\u06af\u0627\u0647\u06cc \u0628\u06cc\u0646\u062f\u0627\u0632\u06cc\u062f \u060c \u0628\u0627\u06cc\u062f \u0631\u062f\u06cc\u0641 \u0647\u0627\u06cc \u062f\u0627\u062f\u0647 \u0627\u06cc \u0645\u0627\u0646\u0646\u062f \u0645\u0648\u0627\u0631\u062f \u0632\u06cc\u0631 \u0631\u0627 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">\u06f6,\u06f1\u06f4\u06f8,\u06f7\u06f2,\u06f3\u06f5,\u06f0,\u06f3\u06f3\u066b\u06f6,\u06f0\u066b\u06f6\u06f2\u06f7,\u06f5\u06f0,\u06f1\n\u06f1,\u06f8\u06f5,\u06f6\u06f6,\u06f2\u06f9,\u06f0,\u06f2\u06f6\u066b\u06f6,\u06f0\u066b\u06f3\u06f5\u06f1,\u06f3\u06f1,\u06f0\n\u06f8,\u06f1\u06f8\u06f3,\u06f6\u06f4,\u06f0,\u06f0,\u06f2\u06f3\u066b\u06f3,\u06f0\u066b\u06f6\u06f7\u06f2,\u06f3\u06f2,\u06f1\n\u06f1,\u06f8\u06f9,\u06f6\u06f6,\u06f2\u06f3,\u06f9\u06f4,\u06f2\u06f8\u066b\u06f1,\u06f0\u066b\u06f1\u06f6\u06f7,\u06f2\u06f1,\u06f0\n\u06f0,\u06f1\u06f3\u06f7,\u06f4\u06f0,\u06f3\u06f5,\u06f1\u06f6\u06f8,\u06f4\u06f3\u066b\u06f1,\u06f2\u066b\u06f2\u06f8\u06f8,\u06f3\u06f3,\u06f1\n...<\/pre>\n<p style=\"text-align: justify;\">\u0627\u06a9\u0646\u0648\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u067e\u0631\u0648\u0646\u062f\u0647 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062a\u0627\u0628\u0639 <a href=\"https:\/\/docs.scipy.org\/doc\/numpy\/reference\/generated\/numpy.loadtxt.html\" target=\"_blank\" rel=\"noopener noreferrer\"> loadtxt()<\/a> \u062f\u0631 NumPy \u0628\u0647 \u0635\u0648\u0631\u062a \u0645\u0627\u062a\u0631\u06cc\u0633 \u0627\u0639\u062f\u0627\u062f \u0628\u0627\u0631\u06af\u06cc\u0631\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0647\u0634\u062a \u0645\u062a\u063a\u06cc\u0631 \u0648\u0631\u0648\u062f\u06cc \u0648 \u06cc\u06a9 \u0645\u062a\u063a\u06cc\u0631 \u062e\u0631\u0648\u062c\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f (\u0633\u062a\u0648\u0646 \u0622\u062e\u0631). \u0645\u0627 \u062f\u0631 \u062d\u0627\u0644 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u062f\u0644\u06cc \u0628\u0631\u0627\u06cc \u062a\u0631\u0633\u06cc\u0645 \u0631\u062f\u06cc\u0641 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc (X) \u0628\u0647 \u06cc\u06a9 \u0645\u062a\u063a\u06cc\u0631 \u062e\u0631\u0648\u062c\u06cc (y) \u062e\u0648\u0627\u0647\u06cc\u0645 \u0628\u0648\u062f \u060c \u06a9\u0647 \u0627\u063a\u0644\u0628 \u0622\u0646\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a y = f (X) \u062e\u0644\u0627\u0635\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0647 \u0635\u0648\u0631\u062a \u0632\u06cc\u0631 \u062e\u0644\u0627\u0635\u0647 \u06a9\u0631\u062f:<\/p>\n<p style=\"text-align: justify;\">\u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc (X):<\/p>\n<ul style=\"text-align: justify;\">\n<li>\u062a\u0639\u062f\u0627\u062f \u062f\u0641\u0639\u0627\u062a \u0628\u0627\u0631\u062f\u0627\u0631\u06cc<\/li>\n<li>\u063a\u0644\u0638\u062a \u06af\u0644\u0648\u06a9\u0632 \u067e\u0644\u0627\u0633\u0645\u0627 \u06f2 \u0633\u0627\u0639\u062a \u062f\u0631 \u06cc\u06a9 \u062a\u0633\u062a \u062a\u062d\u0645\u0644 \u06af\u0644\u0648\u06a9\u0632 \u062e\u0648\u0631\u0627\u06a9\u06cc<\/li>\n<li>\u0641\u0634\u0627\u0631 \u062e\u0648\u0646 \u062f\u06cc\u0627\u0633\u062a\u0648\u0644\u06cc\u06a9 (\u0645\u06cc\u0644\u06cc \u0645\u062a\u0631 \u062c\u06cc\u0648\u0647)<\/li>\n<li>\u0636\u062e\u0627\u0645\u062a \u0686\u06cc\u0646 \u062e\u0648\u0631\u062f\u06af\u06cc \u067e\u0648\u0633\u062a \u0639\u0636\u0644\u0627\u062a \u0633\u0647 \u0633\u0631 (\u0645\u06cc\u0644\u06cc \u0645\u062a\u0631)<\/li>\n<li>\u0627\u0646\u0633\u0648\u0644\u06cc\u0646 \u0633\u0631\u0645\u06cc \u06f2 \u0633\u0627\u0639\u062a\u0647 (mu U\/ml)<\/li>\n<li>\u0634\u0627\u062e\u0635 \u062a\u0648\u062f\u0647 \u0628\u062f\u0646 (\u0648\u0632\u0646 \u062f\u0631 \u06a9\u06cc\u0644\u0648\u06af\u0631\u0645 \/ (\u0642\u062f \u062f\u0631 \u0645\u062a\u0631) ^ \u06f2)<\/li>\n<li>\u0639\u0645\u0644\u06a9\u0631\u062f \u0634\u062c\u0631\u0647 \u0646\u0627\u0645\u0647 \u062f\u06cc\u0627\u0628\u062a<\/li>\n<li>\u0633\u0646 (\u0633\u0627\u0644)<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">\u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u062e\u0631\u0648\u062c\u06cc (y):<\/p>\n<ul style=\"text-align: justify;\">\n<li>\u0645\u062a\u063a\u06cc\u0631 \u06a9\u0644\u0627\u0633 (\u06f0 \u06cc\u0627 \u06f1)<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">\u067e\u0633 \u0627\u0632 \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u067e\u0631\u0648\u0646\u062f\u0647 CSV \u062f\u0631 \u062d\u0627\u0641\u0638\u0647 \u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u062f\u0627\u062f\u0647 \u0631\u0627 \u0628\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0648 \u062e\u0631\u0648\u062c\u06cc \u062a\u0642\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0627\u062f\u0647 \u0647\u0627 \u062f\u0631 \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 \u06f2 \u0628\u0639\u062f\u06cc \u0630\u062e\u06cc\u0631\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0628\u0639\u062f \u0627\u0648\u0644 \u0631\u062f\u06cc\u0641 \u0647\u0627 \u0648 \u0628\u0639\u062f \u062f\u0648\u0645 \u0633\u062a\u0648\u0646 \u0647\u0627 \u0647\u0633\u062a\u0646\u062f \u060c \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644. [rows, columns] .<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0632\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u0633\u062a\u0648\u0646 \u0647\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0639\u0645\u0644\u06af\u0631 \u0628\u0631\u0634 \u0627\u0633\u062a\u0627\u0646\u062f\u0627\u0631\u062f NumPy \u06cc\u0627 &#8221; : &#8221; \u0622\u0631\u0627\u06cc\u0647 \u0631\u0627 \u0628\u0647 \u062f\u0648 \u0622\u0631\u0627\u06cc\u0647 \u062a\u0642\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u0645. \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0628\u0631\u0634 \u06f8: \u06f0 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u06f8 \u0633\u062a\u0648\u0646 \u0627\u0648\u0644 \u0631\u0627 \u0627\u0632 \u0634\u0627\u062e\u0635 \u06f0 \u0628\u0647 \u0646\u0645\u0627\u06cc\u0647 \u06f7 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0646\u06cc\u0645. \u0633\u067e\u0633 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0633\u062a\u0648\u0646 \u062e\u0631\u0648\u062c\u06cc (\u0645\u062a\u063a\u06cc\u0631 \u06f9) \u0631\u0627 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0634\u0627\u062e\u0635 \u06f8 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0646\u06cc\u0645.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# load the dataset\ndataset = loadtxt('pima-indians-diabetes.csv', delimiter=',')\n# split into input (X) and output (y) variables\nX = dataset[:,0:8]\ny = dataset[:,8]\n...<\/pre>\n<p style=\"text-align: justify;\">\u0627\u06a9\u0646\u0648\u0646 \u0622\u0645\u0627\u062f\u0647 \u0627\u06cc\u0645 \u0645\u062f\u0644 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u062e\u0648\u062f \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u060c \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062f\u0627\u0631\u0627\u06cc \u06f9 \u0633\u062a\u0648\u0646 \u0627\u0633\u062a \u0648 \u062f\u0627\u0645\u0646\u0647 \u06f0:\u06f8 \u0633\u062a\u0648\u0646 \u0647\u0627 \u0631\u0627 \u0627\u0632 \u06f0 \u062a\u0627 \u06f7 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u06a9\u0646\u062f \u060c \u0642\u0628\u0644 \u0627\u0632 \u0634\u0627\u062e\u0635 \u06f8 \u0645\u062a\u0648\u0642\u0641 \u0645\u06cc \u0634\u0648\u062f.<\/p>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-2-keras\"><span class=\"ez-toc-section\" id=\"%DB%B2-_%D9%85%D8%AF%D9%84_Keras_%D8%B1%D8%A7_%D8%AA%D8%B9%D8%B1%DB%8C%D9%81_%DA%A9%D9%86%DB%8C%D8%AF\"><\/span><strong>\u06f2- \u0645\u062f\u0644 Keras \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0646\u06cc\u062f<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0645\u062f\u0644 \u0647\u0627 \u062f\u0631 \u06a9\u0631\u0627\u0633 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u062f\u0646\u0628\u0627\u0644\u0647 \u0627\u06cc \u0627\u0632 \u0644\u0627\u06cc\u0647 \u0647\u0627 \u062a\u0639\u0631\u06cc\u0641 \u0645\u06cc \u0634\u0648\u0646\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u06cc\u06a9 <a href=\"https:\/\/keras.io\/models\/sequential\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0645\u062f\u0644 Sequential<\/a> \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0648 \u0644\u0627\u06cc\u0647 \u0647\u0627 \u0631\u0627 \u06cc\u06a9\u06cc \u06cc\u06a9\u06cc \u0627\u0636\u0627\u0641\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u06cc\u0646\u06a9\u0647 \u0627\u0632 \u0645\u0639\u0645\u0627\u0631\u06cc \u0634\u0628\u06a9\u0647 \u062e\u0648\u062f \u0631\u0627\u0636\u06cc \u0628\u0627\u0634\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0627\u0648\u0644\u06cc\u0646 \u0686\u06cc\u0632\u06cc \u06a9\u0647 \u0628\u0627\u06cc\u062f \u062f\u0631\u0633\u062a \u0634\u0648\u062f \u0627\u0637\u0645\u06cc\u0646\u0627\u0646 \u0627\u0632 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0644\u0627\u06cc\u0647 \u0648\u0631\u0648\u062f\u06cc \u0627\u0632 \u062a\u0639\u062f\u0627\u062f \u0648\u0631\u0648\u062f\u06cc \u0647\u0627\u06cc \u0645\u0646\u0627\u0633\u0628 \u0628\u0631\u062e\u0648\u0631\u062f\u0627\u0631 \u0628\u0627\u0634\u062f. \u0627\u06cc\u0646 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0647\u0646\u06af\u0627\u0645 \u0627\u06cc\u062c\u0627\u062f \u0627\u0648\u0644\u06cc\u0646 \u0644\u0627\u06cc\u0647 \u0628\u0627 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 input_dim \u0648 \u062a\u0646\u0638\u06cc\u0645 \u0622\u0646 \u0631\u0648\u06cc \u06f8 \u0628\u0631\u0627\u06cc \u06f8 \u0645\u062a\u063a\u06cc\u0631 \u0648\u0631\u0648\u062f\u06cc \u060c \u062a\u0639\u06cc\u06cc\u0646 \u06a9\u0631\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0686\u06af\u0648\u0646\u0647 \u062a\u0639\u062f\u0627\u062f \u0644\u0627\u06cc\u0647 \u0647\u0627 \u0648 \u0627\u0646\u0648\u0627\u0639 \u0622\u0646 \u0647\u0627 \u0631\u0627 \u0628\u062f\u0627\u0646\u06cc\u0645\u061f<\/p>\n<p style=\"text-align: justify;\">\u0627\u06cc\u0646 \u0633\u0648\u0627\u0644 \u0628\u0633\u06cc\u0627\u0631 \u0633\u062e\u062a\u06cc \u0627\u0633\u062a. \u0631\u0648\u0634 \u0647\u0627\u06cc \u0627\u0628\u062a\u06a9\u0627\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u0632 \u0622\u0646 \u0647\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645 \u0648 \u063a\u0627\u0644\u0628\u0627\u064b \u0628\u0647\u062a\u0631\u06cc\u0646 \u0633\u0627\u062e\u062a\u0627\u0631 \u0634\u0628\u06a9\u0647 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u06cc\u06a9 \u0622\u0632\u0645\u0627\u06cc\u0634 \u0622\u0632\u0645\u0648\u0646 \u0648 \u062e\u0637\u0627 \u06cc\u0627\u0641\u062a \u0645\u06cc \u0634\u0648\u062f . \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u060c \u0634\u0645\u0627 \u0628\u0647 \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0628\u0647 \u0627\u0646\u062f\u0627\u0632\u0647 \u06a9\u0627\u0641\u06cc \u0628\u0632\u0631\u06af \u0646\u06cc\u0627\u0632 \u062f\u0627\u0631\u06cc\u062f \u062a\u0627 \u0633\u0627\u062e\u062a\u0627\u0631 \u0645\u0634\u06a9\u0644 \u0631\u0627 \u062f\u0631\u06a9 \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0631 \u0627\u06cc\u0646 \u0645\u062b\u0627\u0644 \u060c \u0645\u0627 \u0627\u0632 \u06cc\u06a9 \u0633\u0627\u062e\u062a\u0627\u0631 \u0634\u0628\u06a9\u0647 \u06a9\u0627\u0645\u0644\u0627\u064b \u0645\u062a\u0635\u0644 \u0628\u0627 \u0633\u0647 \u0644\u0627\u06cc\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0644\u0627\u06cc\u0647 \u0647\u0627\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0645\u062a\u0635\u0644 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <a href=\"https:\/\/keras.io\/layers\/core\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u06a9\u0644\u0627\u0633 Dense<\/a> \u062a\u0639\u0631\u06cc\u0641 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u062a\u0639\u062f\u0627\u062f \u0646\u0648\u0631\u0648\u0646 \u0647\u0627 \u06cc\u0627 \u06af\u0631\u0647 \u0647\u0627\u06cc \u0645\u0648\u062c\u0648\u062f \u062f\u0631 \u0644\u0627\u06cc\u0647 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0627\u0648\u0644\u06cc\u0646 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u0645 \u0648 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc \u060c \u062a\u0627\u0628\u0639 \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0627\u0632 \u062a\u0627\u0628\u0639 \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc \u0648\u0627\u062d\u062f \u062e\u0637\u06cc \u0627\u0635\u0644\u0627\u062d \u0634\u062f\u0647 \u062f\u0631 \u062f\u0648 \u0644\u0627\u06cc\u0647 \u0627\u0648\u0644 \u0648 \u062a\u0627\u0628\u0639 Sigmoid \u062f\u0631 \u0644\u0627\u06cc\u0647 \u062e\u0631\u0648\u062c\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0642\u0628\u0644\u0627\u064b \u0627\u06cc\u0646\u06af\u0648\u0646\u0647 \u0628\u0648\u062f \u06a9\u0647 \u062a\u0648\u0627\u0628\u0639 \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc Sigmoid \u0648 Tanh \u0628\u0631\u0627\u06cc \u0647\u0645\u0647 \u0644\u0627\u06cc\u0647 \u0647\u0627 \u062a\u0631\u062c\u06cc\u062d \u062f\u0627\u062f\u0647 \u0645\u06cc \u0634\u062f\u0646\u062f. \u0627\u06cc\u0646 \u0631\u0648\u0632\u0647\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062a\u0627\u0628\u0639 \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc ReLU \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647\u062a\u0631\u06cc \u062d\u0627\u0635\u0644 \u0645\u06cc \u0634\u0648\u062f. \u0645\u0627 \u0628\u0631\u0627\u06cc \u0627\u0637\u0645\u06cc\u0646\u0627\u0646 \u0627\u0632 \u0627\u06cc\u0646\u06a9\u0647 \u062e\u0631\u0648\u062c\u06cc \u0634\u0628\u06a9\u0647 \u0645\u0627 \u0628\u06cc\u0646 \u06f0 \u062a\u0627 \u06f1 \u0627\u0633\u062a \u060c \u0627\u0632 Sigmoid \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0648 \u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u0627\u0632 \u06a9\u0644\u0627\u0633 \u06f1 \u06cc\u0627 \u0628\u0647 \u06cc\u06a9 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0633\u062e\u062a \u0627\u0632 \u0647\u0631 \u062f\u0648 \u06a9\u0644\u0627\u0633 \u0628\u0627 \u0622\u0633\u062a\u0627\u0646\u0647 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u06f0\u066b\u06f5 \u060c \u0622\u0633\u0627\u0646 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u0628\u0627 \u0627\u0641\u0632\u0648\u062f\u0646 \u0647\u0631 \u0644\u0627\u06cc\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0647\u0645\u0647 \u0622\u0646 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0647\u0645 \u062a\u06a9\u0647 \u062a\u06a9\u0647 \u06a9\u0646\u06cc\u0645:<\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"text-align: justify;\">\u0645\u062f\u0644 \u0627\u0646\u062a\u0638\u0627\u0631 \u062f\u0627\u0631\u062f \u0631\u062f\u06cc\u0641 \u0647\u0627\u06cc \u062f\u0627\u062f\u0647 \u0628\u0627 \u06f8 \u0645\u062a\u063a\u06cc\u0631 (\u0627\u0633\u062a\u062f\u0644\u0627\u0644 input_dim = 8) \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u062f.<\/li>\n<li style=\"text-align: justify;\">\u0627\u0648\u0644\u06cc\u0646 \u0644\u0627\u06cc\u0647 \u0645\u062e\u0641\u06cc \u062f\u0627\u0631\u0627\u06cc \u06f1\u06f2 \u06af\u0631\u0647 \u0627\u0633\u062a \u0648 \u0627\u0632 \u0639\u0645\u0644\u06a9\u0631\u062f \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc relu \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.<\/li>\n<li style=\"text-align: justify;\">\u0644\u0627\u06cc\u0647 \u0645\u062e\u0641\u06cc \u062f\u0648\u0645 \u062f\u0627\u0631\u0627\u06cc \u06f8 \u06af\u0631\u0647 \u0627\u0633\u062a \u0648 \u0627\u0632 \u0639\u0645\u0644\u06a9\u0631\u062f \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc relu \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.<\/li>\n<li style=\"text-align: justify;\">\u0644\u0627\u06cc\u0647 \u062e\u0631\u0648\u062c\u06cc \u062f\u0627\u0631\u0627\u06cc \u06cc\u06a9 \u06af\u0631\u0647 \u0627\u0633\u062a \u0648 \u0627\u0632 \u0639\u0645\u0644\u06a9\u0631\u062f \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc Sigmoid \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.<\/li>\n<\/ul>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# define the keras model\nmodel = Sequential()\nmodel.add(Dense(12, input_dim=8, activation='relu'))\nmodel.add(Dense(8, activation='relu'))\nmodel.add(Dense(1, activation='sigmoid'))\n...<\/pre>\n<p style=\"text-align: justify;\">\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u060c \u06af\u06cc\u062c \u06a9\u0646\u0646\u062f\u0647 \u062a\u0631\u06cc\u0646 \u0686\u06cc\u0632 \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0634\u06a9\u0644 \u0648\u0631\u0648\u062f\u06cc \u0645\u062f\u0644 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0631\u0648\u06cc \u0627\u0648\u0644\u06cc\u0646 \u0644\u0627\u06cc\u0647 \u067e\u0646\u0647\u0627\u0646 \u062a\u0639\u0631\u06cc\u0641 \u0634\u062f\u0647 \u0627\u0633\u062a. \u0627\u06cc\u0646 \u0628\u062f\u0627\u0646 \u0645\u0639\u0646\u06cc \u0627\u0633\u062a \u06a9\u0647 \u062e\u0637 \u06a9\u062f\u06cc \u06a9\u0647 \u0627\u0648\u0644\u06cc\u0646 \u0644\u0627\u06cc\u0647 Dense \u0631\u0627 \u0627\u0636\u0627\u0641\u0647 \u0645\u06cc \u06a9\u0646\u062f \u060c \u06f2 \u06a9\u0627\u0631 \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc \u062f\u0647\u062f \u060c \u062a\u0639\u0631\u06cc\u0641 \u0644\u0627\u06cc\u0647 \u0648\u0631\u0648\u062f\u06cc \u06cc\u0627 \u0642\u0627\u0628\u0644 \u0645\u0634\u0627\u0647\u062f\u0647 \u0648 \u062a\u0639\u0631\u06cc\u0641 \u0627\u0648\u0644\u06cc\u0646 \u0644\u0627\u06cc\u0647 \u0645\u062e\u0641\u06cc \u0627\u0633\u062a.<\/p>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-3-keras\"><span class=\"ez-toc-section\" id=\"%DB%B3-_%D9%85%D8%AF%D9%84_Keras_%D8%B1%D8%A7_%DA%A9%D8%A7%D9%85%D9%BE%D8%A7%DB%8C%D9%84_%DA%A9%D9%86%DB%8C%D8%AF\"><\/span><strong>\u06f3- \u0645\u062f\u0644 Keras \u0631\u0627 \u06a9\u0627\u0645\u067e\u0627\u06cc\u0644 \u06a9\u0646\u06cc\u062f<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0627\u06a9\u0646\u0648\u0646 \u06a9\u0647 \u0645\u062f\u0644 \u062a\u0639\u0631\u06cc\u0641 \u0634\u062f \u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0622\u0646 \u0631\u0627 \u06a9\u0627\u0645\u067e\u0627\u06cc\u0644 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0631 \u062a\u062f\u0648\u06cc\u0646 \u0645\u062f\u0644 \u0627\u0632 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0647\u0627\u06cc \u0639\u062f\u062f\u06cc \u06a9\u0627\u0631\u0622\u0645\u062f \u062f\u0631 \u0632\u06cc\u0631 \u067e\u0648\u0634\u0634 (\u0627\u0635\u0637\u0644\u0627\u062d\u0627\u064b \u0628\u0627\u0637\u0646) \u0645\u0627\u0646\u0646\u062f Theano \u06cc\u0627 TensorFlow \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f. Backend \u0628\u0647 \u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0631\u0648\u0634 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0646\u0645\u0627\u06cc\u0634 \u0634\u0628\u06a9\u0647 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0648 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0628\u0631\u0627\u06cc \u0627\u062c\u0631\u0627 \u0628\u0631 \u0631\u0648\u06cc \u0633\u062e\u062a \u0627\u0641\u0632\u0627\u0631 \u0634\u0645\u0627 \u0645\u0627\u0646\u0646\u062f CPU \u06cc\u0627 GPU \u06cc\u0627 \u062d\u062a\u06cc \u062a\u0648\u0632\u06cc\u0639 \u0634\u062f\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0647\u0646\u06af\u0627\u0645 \u06a9\u0627\u0645\u067e\u0627\u06cc\u0644 \u06a9\u0631\u062f\u0646 \u060c \u0628\u0627\u06cc\u062f \u0628\u0631\u062e\u06cc \u062e\u0635\u0648\u0635\u06cc\u0627\u062a \u0627\u0636\u0627\u0641\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0647\u0646\u06af\u0627\u0645 \u0622\u0645\u0648\u0632\u0634 \u0634\u0628\u06a9\u0647 \u0631\u0627 \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u0645. \u0628\u0647 \u06cc\u0627\u062f \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u0622\u0645\u0648\u0632\u0634 \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0628\u0647 \u0645\u0639\u0646\u0627\u06cc \u06cc\u0627\u0641\u062a\u0646 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u0632\u0646 \u0628\u0631\u0627\u06cc \u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc \u0627\u0632 \u0648\u0631\u0648\u062f\u06cc \u0647\u0627 \u0628\u0631\u0627\u06cc \u062e\u0631\u0648\u062c\u06cc \u0647\u0627 \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u0627 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0628\u0627\u06cc\u062f \u062a\u0627\u0628\u0639 loss (\u062a\u0627\u0628\u0639 \u0632\u06cc\u0627\u0646) \u0631\u0627 \u062a\u0639\u06cc\u06cc\u0646 \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u06cc \u0627\u0632 \u0648\u0632\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u0648\u062f \u060c \u0627\u0632 \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632 \u0628\u0631\u0627\u06cc \u062c\u0633\u062a\u062c\u0648\u06cc \u062f\u0631 \u0648\u0632\u0646 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0634\u0628\u06a9\u0647 \u0648 \u0647\u0631 \u0645\u0639\u06cc\u0627\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f \u06a9\u0647 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u0631 \u0637\u0648\u0644 \u0622\u0645\u0648\u0632\u0634 \u062c\u0645\u0639 \u0622\u0648\u0631\u06cc \u0648 \u06af\u0632\u0627\u0631\u0634 \u062f\u0647\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0631 \u0627\u06cc\u0646 \u062d\u0627\u0644\u062a \u060c \u0627\u0632 \u0622\u0646\u062a\u0631\u0648\u067e\u06cc \u0645\u062a\u0642\u0627\u0628\u0644 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0636\u0631\u0631 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f. \u0627\u06cc\u0646 \u0627\u0632 \u062f\u0633\u062a \u062f\u0627\u062f\u0646 \u0628\u0631\u0627\u06cc \u0645\u0634\u06a9\u0644\u0627\u062a \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0628\u0627\u06cc\u0646\u0631\u06cc \u0627\u0633\u062a \u0648 \u062f\u0631 Keras \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 &#8220;\u0628\u0627\u06cc\u0646\u0631\u06cc_ \u06a9\u0631\u0627\u0633\u0646\u0631\u0648\u067e\u06cc&#8221; \u062a\u0639\u0631\u06cc\u0641 \u0634\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632 \u0631\u0627 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0641\u0631\u0648\u062f \u0634\u06cc\u0628 \u062a\u0635\u0627\u062f\u0641\u06cc \u06a9\u0627\u0631\u0622\u0645\u062f &#8220;adam&#8221; \u062a\u0639\u0631\u06cc\u0641 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f. \u0627\u06cc\u0646 \u06cc\u06a9 \u0646\u0633\u062e\u0647 \u0645\u062d\u0628\u0648\u0628 \u0627\u0632 \u0634\u06cc\u0628 \u0646\u0632\u0648\u0644\u06cc \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 \u0628\u0647 \u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u062e\u0648\u062f \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u062f\u0631 \u0637\u06cc\u0641 \u06af\u0633\u062a\u0631\u062f\u0647 \u0627\u06cc \u0627\u0632 \u0645\u0634\u06a9\u0644\u0627\u062a \u0646\u062a\u0627\u06cc\u062c \u062e\u0648\u0628\u06cc \u0645\u06cc \u062f\u0647\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0633\u0631\u0627\u0646\u062c\u0627\u0645 \u060c \u0686\u0648\u0646 \u06cc\u06a9 \u0645\u0634\u06a9\u0644 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0627\u0633\u062a \u060c \u0645\u0627 \u0635\u062d\u062a \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0631\u0627 \u06a9\u0647 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0645\u062a\u0631\u06cc\u06a9 \u062a\u0639\u0631\u06cc\u0641 \u0634\u062f\u0647\u060c \u062c\u0645\u0639 \u0622\u0648\u0631\u06cc \u0648 \u06af\u0632\u0627\u0631\u0634 \u0645\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# compile the keras model\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n...<\/pre>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-4-fit-keras\"><span class=\"ez-toc-section\" id=\"%DB%B4-_Fit_%DA%A9%D8%B1%D8%AF%D9%86_%D8%A8%D8%A7_%D9%85%D8%AF%D9%84_Keras\"><\/span><strong>\u06f4- Fit \u06a9\u0631\u062f\u0646 \u0628\u0627 \u0645\u062f\u0644 Keras<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0645\u0627 \u0645\u062f\u0644 \u062e\u0648\u062f \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0631\u062f\u0647 \u0648 \u0622\u0646 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0645\u062d\u0627\u0633\u0628\u0647 \u06a9\u0627\u0631\u0622\u0645\u062f \u0622\u0645\u0627\u062f\u0647 \u06a9\u0631\u062f\u0647 \u0627\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0627\u06a9\u0646\u0648\u0646 \u0632\u0645\u0627\u0646 \u0627\u062c\u0631\u0627\u06cc \u0645\u062f\u0644 \u0628\u0631 \u0631\u0648\u06cc \u0628\u0631\u062e\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0641\u0631\u0627 \u0631\u0633\u06cc\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0627 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u062a\u0627\u0628\u0639 fit()\u060c \u0645\u062f\u0644 \u062e\u0648\u062f \u0631\u0627 \u0628\u0631 \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u0634\u062f\u0647 \u062e\u0648\u062f \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u0645 \u06cc\u0627 \u0645\u062a\u0646\u0627\u0633\u0628 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0622\u0645\u0648\u0632\u0634 \u062f\u0631 \u062f\u0648\u0631\u0647 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0631\u062e \u0645\u06cc \u062f\u0647\u062f \u0648 \u0647\u0631 \u062f\u0648\u0631\u0647 \u0628\u0647 \u0686\u0646\u062f \u062f\u0633\u062a\u0647 \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc \u0634\u0648\u062f.<\/p>\n<ul>\n<li style=\"text-align: justify;\"><strong>Epoch :<\/strong> \u06cc\u06a9 \u0631\u062f\u06cc\u0641 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u0645\u06cc \u06a9\u0646\u062f.<\/li>\n<li style=\"text-align: justify;\"><strong>Batch :<\/strong> \u06cc\u06a9 \u06cc\u0627 \u0686\u0646\u062f \u0646\u0645\u0648\u0646\u0647 \u0642\u0628\u0644 \u0627\u0632 \u0628\u0647 \u0631\u0648\u0632\u0631\u0633\u0627\u0646\u06cc \u0648\u0632\u0646 \u060c \u062a\u0648\u0633\u0637 \u0645\u062f\u0644 \u062f\u0631 \u06cc\u06a9 \u062f\u0648\u0631\u0647 \u062f\u0631 \u0646\u0638\u0631 \u06af\u0631\u0641\u062a\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">\u06cc\u06a9 \u062f\u0648\u0631\u0647 \u0627\u0632 \u06cc\u06a9 \u06cc\u0627 \u0686\u0646\u062f \u062f\u0633\u062a\u0647 \u062a\u0634\u06a9\u06cc\u0644 \u0634\u062f\u0647 \u0627\u0633\u062a \u060c \u0628\u0631 \u0627\u0633\u0627\u0633 \u0627\u0646\u062f\u0627\u0632\u0647 \u062f\u0633\u062a\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u0648 \u0645\u062f\u0644 \u0645\u0646\u0627\u0633\u0628 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062f\u0648\u0631\u0647 \u0647\u0627 \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u0631\u0648\u0646\u062f \u0622\u0645\u0648\u0632\u0634 \u0628\u0631\u0627\u06cc \u062a\u0639\u062f\u0627\u062f \u0645\u0634\u062e\u0635\u06cc \u0627\u0632 \u062a\u06a9\u0631\u0627\u0631\u0647\u0627 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u06cc \u0628\u0647 \u0646\u0627\u0645 epochs \u0627\u062c\u0631\u0627 \u0645\u06cc \u0634\u0648\u062f \u06a9\u0647 \u0628\u0627\u06cc\u062f \u0622\u0646 \u0647\u0627 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 epochs \u0645\u0634\u062e\u0635 \u06a9\u0646\u06cc\u0645. \u0647\u0645\u0686\u0646\u06cc\u0646 \u0628\u0627\u06cc\u062f \u062a\u0639\u062f\u0627\u062f \u0631\u062f\u06cc\u0641 \u0647\u0627\u06cc \u062f\u0627\u062f\u0647 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u0645 \u06a9\u0647 \u0642\u0628\u0644 \u0627\u0632 \u0628\u0647 \u0631\u0648\u0632\u0631\u0633\u0627\u0646\u06cc \u0648\u0632\u0646 \u0645\u062f\u0644 \u0647\u0627 \u062f\u0631 \u0647\u0631 \u062f\u0648\u0631\u0647 \u062f\u0631 \u0646\u0638\u0631 \u06af\u0631\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f \u060c \u0627\u0646\u062f\u0627\u0632\u0647 \u062f\u0633\u062a\u0647 \u0627\u06cc \u0646\u0627\u0645\u06cc\u062f\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f \u0648 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 batch_size \u062a\u0646\u0638\u06cc\u0645 \u0645\u06cc \u0634\u0648\u0646\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0645\u0634\u06a9\u0644 \u060c \u0645\u0627 \u0628\u0631\u0627\u06cc \u062a\u0639\u062f\u0627\u062f \u06a9\u0645\u06cc \u062f\u0648\u0631\u0647 (\u06f1\u06f5\u06f0) \u0627\u062c\u0631\u0627 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u0648 \u0627\u0632 \u0627\u0646\u062f\u0627\u0632\u0647 \u062f\u0633\u062a\u0647 \u0627\u06cc \u0646\u0633\u0628\u062a\u0627\u064b \u06a9\u0645 \u06f1\u06f0 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0627\u06cc\u0646 \u062a\u0646\u0638\u06cc\u0645\u0627\u062a \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0632\u0645\u0648\u0646 \u0648 \u062e\u0637\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0631\u062f. \u0645\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u0645 \u0645\u062f\u0644 \u0631\u0627 \u0628\u0647 \u0627\u0646\u062f\u0627\u0632\u0647 \u06a9\u0627\u0641\u06cc \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u0645 \u062a\u0627 \u0628\u062a\u0648\u0627\u0646\u062f \u0627\u0632 \u0631\u062f\u06cc\u0641 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0628\u0647 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u062e\u0631\u0648\u062c\u06cc \u060c \u0646\u06af\u0627\u0634\u062a \u062e\u0648\u0628 (\u06cc\u0627 \u0628\u0647 \u0627\u0646\u062f\u0627\u0632\u0647 \u06a9\u0627\u0641\u06cc \u062e\u0648\u0628) \u0631\u0627 \u0628\u06cc\u0627\u0645\u0648\u0632\u062f. \u0627\u06cc\u0646 \u0645\u062f\u0644 \u0647\u0645\u06cc\u0634\u0647 \u062f\u0627\u0631\u0627\u06cc \u0628\u0631\u062e\u06cc \u062e\u0637\u0627 \u0647\u0627 \u0627\u0633\u062a \u060c \u0627\u0645\u0627 \u0645\u0642\u062f\u0627\u0631 \u062e\u0637\u0627 \u067e\u0633 \u0627\u0632 \u0645\u062f\u062a\u06cc \u0628\u0631\u0627\u06cc \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u0645\u062f\u0644 \u0645\u0639\u06cc\u0646 \u06a9\u0627\u0647\u0634 \u0645\u06cc \u06cc\u0627\u0628\u062f. \u0628\u0647 \u0627\u06cc\u0646 \u0631\u0648\u0634\u060c \u0647\u0645\u06af\u0631\u0627\u06cc\u06cc \u0645\u062f\u0644 \u06af\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u062f.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# fit the keras model on the dataset\nmodel.fit(X, y, epochs=150, batch_size=10)\n...<\/pre>\n<p style=\"text-align: justify;\">\u0627\u06cc\u0646 \u062c\u0627\u06cc\u06cc \u0627\u0633\u062a \u06a9\u0647 \u06a9\u0627\u0631 \u0631\u0648\u06cc CPU \u06cc\u0627 GPU \u0634\u0645\u0627 \u0627\u062a\u0641\u0627\u0642 \u0645\u06cc \u0627\u0641\u062a\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0645\u062b\u0627\u0644 GPU \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0646\u06cc\u0633\u062a .<\/p>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-5-keras\"><span class=\"ez-toc-section\" id=\"%DB%B5-_%D9%85%D8%AF%D9%84_Keras_%D8%B1%D8%A7_%D8%A7%D8%B1%D8%B2%DB%8C%D8%A7%D8%A8%DB%8C_%DA%A9%D9%86%DB%8C%D8%AF\"><\/span><strong>\u06f5- \u0645\u062f\u0644 Keras \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u06cc\u062f<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0645\u0627 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u062e\u0648\u062f \u0631\u0627 \u062f\u0631 \u06a9\u0644 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u062f\u0647 \u0627\u06cc\u0645 \u0648 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0639\u0645\u0644\u06a9\u0631\u062f \u0634\u0628\u06a9\u0647 \u0631\u0627 \u062f\u0631 \u0647\u0645\u0627\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0641\u0642\u0637 \u0628\u0647 \u0645\u0627 \u0627\u06cc\u062f\u0647 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0645\u0627 \u0686\u0642\u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0645\u062f\u0644\u0633\u0627\u0632\u06cc \u06a9\u0631\u062f\u0647 \u0627\u06cc\u0645 (\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644 \u062f\u0642\u062a \u0622\u0645\u0648\u0632\u0634) \u060c \u0627\u0645\u0627 \u0647\u06cc\u0686 \u0627\u06cc\u062f\u0647 \u0627\u06cc \u062f\u0631\u0628\u0627\u0631\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062c\u062f\u06cc\u062f \u0646\u062f\u0627\u0631\u06cc\u0645. \u0645\u0627 \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0633\u0627\u062f\u06af\u06cc \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f\u0647 \u0627\u06cc\u0645 \u060c \u0627\u0645\u0627 \u062f\u0631 \u062d\u0627\u0644\u062a \u0627\u06cc\u062f\u0647 \u0622\u0644 \u060c \u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0648 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u062f\u0644 \u062e\u0648\u062f \u062a\u0641\u06a9\u06cc\u06a9 \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062a\u0627\u0628\u0639 () evaluate \u0628\u0631 \u0631\u0648\u06cc \u0645\u062f\u0644 \u062e\u0648\u062f \u0645\u062f\u0644 \u062e\u0648\u062f \u0631\u0627 \u0628\u0631 \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u062e\u0648\u062f \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0631\u062f\u0647 \u0648 \u0627\u0632 \u0647\u0645\u0627\u0646 \u0648\u0631\u0648\u062f\u06cc \u0648 \u062e\u0631\u0648\u062c\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0627\u06cc\u0646 \u06cc\u06a9 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0641\u062a \u0648\u0631\u0648\u062f\u06cc \u0648 \u062e\u0631\u0648\u062c\u06cc \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0627\u0645\u062a\u06cc\u0627\u0632\u0627\u062a \u0631\u0627 \u062c\u0645\u0639 \u0645\u06cc \u06a9\u0646\u062f \u060c \u0627\u0632 \u062c\u0645\u0644\u0647 \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u062a\u0627\u0628\u0639 \u0632\u06cc\u0627\u0646 \u0648 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u06a9\u0631\u062f\u0647 \u0627\u06cc\u062f \u060c \u0645\u0627\u0646\u0646\u062f \u062f\u0642\u062a.<\/p>\n<p style=\"text-align: justify;\">\u062a\u0627\u0628\u0639 evaluate() \u0644\u06cc\u0633\u062a\u06cc \u0631\u0627 \u0628\u0627 \u062f\u0648 \u0645\u0642\u062f\u0627\u0631 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f. \u0645\u0648\u0631\u062f \u0627\u0648\u0644 \u0632\u06cc\u0627\u0646 \u0645\u062f\u0644 \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0648 \u062f\u0648\u0645 \u062f\u0642\u062a \u0645\u062f\u0644 \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f. \u0645\u0627 \u0641\u0642\u0637 \u0639\u0644\u0627\u0642\u0647 \u0645\u0646\u062f \u0628\u0647 \u06af\u0632\u0627\u0631\u0634 \u0635\u062d\u062a \u0647\u0633\u062a\u06cc\u0645 \u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631 \u0636\u0631\u0631 \u0631\u0627 \u0646\u0627\u062f\u06cc\u062f\u0647 \u0645\u06cc \u06af\u06cc\u0631\u06cc\u0645.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# evaluate the keras model\n_, accuracy = model.evaluate(X, y)\nprint('Accuracy: %.2f' % (accuracy*100))<\/pre>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-6\"><span class=\"ez-toc-section\" id=\"%DB%B6-_%D9%87%D9%85%D9%87_%D8%B1%D8%A7_%D8%A8%D8%A7_%D9%87%D9%85_%D8%AA%D8%AC%D9%85%DB%8C%D8%B9_%DA%A9%D9%86%DB%8C%D8%AF\"><\/span><strong>\u06f6- \u0647\u0645\u0647 \u0631\u0627 \u0628\u0627 \u0647\u0645 \u062a\u062c\u0645\u06cc\u0639 \u06a9\u0646\u06cc\u062f<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0634\u0645\u0627 \u062a\u0627 \u0627\u06cc\u0646\u062c\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u062f\u06cc\u062f\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u0627\u0648\u0644\u06cc\u0646 \u0645\u062f\u0644 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u062e\u0648\u062f \u0631\u0627 \u062f\u0631 \u06a9\u0631\u0627\u0633 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u06cc\u0627\u06cc\u06cc\u062f \u0647\u0645\u0647 \u0631\u0627 \u0628\u0627 \u0647\u0645 \u062f\u0631 \u06cc\u06a9 \u0645\u062b\u0627\u0644 \u06a9\u062f\u0646\u0648\u06cc\u0633\u06cc \u06a9\u0627\u0645\u0644 \u06af\u0631\u0647 \u0628\u0632\u0646\u06cc\u0645.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># first neural network with keras tutorial\nfrom numpy import loadtxt\nfrom keras.models import Sequential\nfrom keras.layers import Dense\n# load the dataset\ndataset = loadtxt('pima-indians-diabetes.csv', delimiter=',')\n# split into input (X) and output (y) variables\nX = dataset[:,0:8]\ny = dataset[:,8]\n# define the keras model\nmodel = Sequential()\nmodel.add(Dense(12, input_dim=8, activation='relu'))\nmodel.add(Dense(8, activation='relu'))\nmodel.add(Dense(1, activation='sigmoid'))\n# compile the keras model\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n# fit the keras model on the dataset\nmodel.fit(X, y, epochs=150, batch_size=10)\n# evaluate the keras model\n_, accuracy = model.evaluate(X, y)\nprint('Accuracy: %.2f' % (accuracy*100))<\/pre>\n<p style=\"text-align: justify;\">\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0647\u0645\u0647 \u06a9\u062f\u0647\u0627 \u0631\u0627 \u062f\u0631 \u067e\u0631\u0648\u0646\u062f\u0647 Python \u062e\u0648\u062f \u06a9\u067e\u06cc \u06a9\u0631\u062f\u0647 \u0648 \u0628\u0627 \u0639\u0646\u0648\u0627\u0646 &#8220;keras_first_network.py&#8221; \u062f\u0631 \u0647\u0645\u0627\u0646 \u062f\u0627\u06cc\u0631\u06a9\u062a\u0648\u0631\u06cc \u067e\u0631\u0648\u0646\u062f\u0647 \u062f\u0627\u062f\u0647 &#8220;pima-indians-diabet.csv&#8221; \u0630\u062e\u06cc\u0631\u0647 \u06a9\u0646\u06cc\u062f. \u0633\u067e\u0633 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0641\u0627\u06cc\u0644 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0627\u0632 \u062e\u0637 \u0641\u0631\u0645\u0627\u0646 \u062e\u0648\u062f \u0628\u0647 \u0634\u0631\u062d \u0632\u06cc\u0631 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">python keras_first_network.py<\/pre>\n<p style=\"text-align: justify;\">\u0628\u0627 \u0627\u062c\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0645\u062b\u0627\u0644 \u060c \u0628\u0627\u06cc\u062f \u067e\u06cc\u0627\u0645\u06cc \u0631\u0627 \u0628\u0631\u0627\u06cc \u0647\u0631 \u06f1\u06f5\u06f0 \u062f\u0648\u0631\u0647 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0645\u06cc\u0632\u0627\u0646 \u0632\u06cc\u0627\u0646 \u0648 \u062f\u0642\u062a \u0631\u0627 \u0686\u0627\u067e \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0628\u0647 \u062f\u0646\u0628\u0627\u0644 \u0622\u0646 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0646\u0647\u0627\u06cc\u06cc \u0645\u062f\u0644 \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u062f\u0647 \u0634\u062f\u0647 \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0627\u0633\u062a.<\/p>\n<p style=\"text-align: justify;\">\u062d\u062f\u0648\u062f \u06f1\u06f0 \u062b\u0627\u0646\u06cc\u0647 \u0637\u0648\u0644 \u0645\u06cc \u06a9\u0634\u062f \u062a\u0627 \u062f\u0631 \u0633\u06cc\u0633\u062a\u0645 \u0645\u0646 \u06a9\u0647 \u0631\u0648\u06cc CPU \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f \u060c \u0627\u062c\u0631\u0627 \u0634\u0648\u062f.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0631 \u062d\u0627\u0644\u062a \u0627\u06cc\u062f\u0647 \u0622\u0644 \u060c \u0645\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u0645 \u0636\u0631\u0631 \u0628\u0647 \u0635\u0641\u0631 \u0628\u0631\u0633\u062f \u0648 \u062f\u0642\u062a \u0628\u0647 \u06f1\u066b\u06f0 (\u0645\u062b\u0644\u0627\u064b \u06f1\u06f0\u06f0\u066a) \u0628\u0631\u0633\u062f. \u0627\u06cc\u0646 \u0645\u0633\u0626\u0644\u0647 \u0628\u0631\u0627\u06cc \u0647\u06cc\u0686 \u06cc\u06a9 \u0627\u0632 \u067e\u06cc\u0634 \u067e\u0627 \u0627\u0641\u062a\u0627\u062f\u0647 \u062a\u0631\u06cc\u0646 \u0645\u0634\u06a9\u0644\u0627\u062a \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0627\u0645\u06a9\u0627\u0646 \u067e\u0630\u06cc\u0631 \u0646\u06cc\u0633\u062a. \u062f\u0631 \u0639\u0648\u0636 \u060c \u0645\u0627 \u0647\u0645\u06cc\u0634\u0647 \u062f\u0631 \u0645\u062f\u0644 \u062e\u0648\u062f \u0645\u0642\u062f\u0627\u0631\u06cc \u062e\u0637\u0627 \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u0627\u0634\u062a. \u0647\u062f\u0641 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u06cc\u06a9 \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u0645\u062f\u0644 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0646\u06cc\u062f \u0648 \u0645\u062f\u0644 \u0631\u0627 \u0628\u0631\u0627\u06cc \u062f\u0633\u062a\u06cc\u0627\u0628\u06cc \u0628\u0647 \u06a9\u0645\u062a\u0631\u06cc\u0646 \u0627\u0641\u062a \u0648 \u0628\u0627\u0644\u0627\u062a\u0631\u06cc\u0646 \u062f\u0642\u062a \u0645\u0645\u06a9\u0646 \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u0634\u062e\u0635 \u060c \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u062f.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n\u06f7\u06f6\u06f8\/\u06f7\u06f6\u06f8 [==============================] - \u06f0s 63us\/step - loss: 0.4817 - acc: 0.7708\nEpoch 147\/150\n\u06f7\u06f6\u06f8\/\u06f7\u06f6\u06f8 [==============================] - \u06f0s 63us\/step - loss: 0.4764 - acc: 0.7747\nEpoch 148\/150\n\u06f7\u06f6\u06f8\/\u06f7\u06f6\u06f8 [==============================] - \u06f0s 63us\/step - loss: 0.4737 - acc: 0.7682\nEpoch 149\/150\n\u06f7\u06f6\u06f8\/\u06f7\u06f6\u06f8 [==============================] - \u06f0s 64us\/step - loss: 0.4730 - acc: 0.7747\nEpoch 150\/150\n\u06f7\u06f6\u06f8\/\u06f7\u06f6\u06f8 [==============================] - \u06f0s 63us\/step - loss: 0.4754 - acc: 0.7799\n\u06f7\u06f6\u06f8\/\u06f7\u06f6\u06f8 [==============================] - \u06f0s 38us\/step\nAccuracy: 76.56<\/pre>\n<p style=\"text-align: justify;\">\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u060c \u0627\u06af\u0631 \u0627\u06cc\u0646 \u0645\u062b\u0627\u0644 \u0631\u0627 \u062f\u0631 \u0646\u0648\u062a \u0628\u0648\u06a9 IPython \u06cc\u0627 Jupyter \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f \u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u062e\u0637\u0627 \u062f\u0631\u06cc\u0627\u0641\u062a \u0634\u0648\u062f.<\/p>\n<p style=\"text-align: justify;\">\u062f\u0644\u06cc\u0644 \u0622\u0646 \u0645\u06cc\u0644\u0647 \u0647\u0627\u06cc \u067e\u06cc\u0634\u0631\u0641\u062a \u062e\u0631\u0648\u062c\u06cc \u062f\u0631 \u062d\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0627\u0633\u062a. \u0628\u0627 \u062a\u0646\u0638\u06cc\u0645 verbose = 0 \u062f\u0631 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u062a\u0648\u0627\u0628\u0639 fit () \u0648 evaluate () \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u0627\u06cc\u0646 \u0645\u0648\u0627\u0631\u062f \u0631\u0627 \u06a9\u0645 \u06a9\u0646\u06cc\u062f \u060c \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# fit the keras model on the dataset without progress bars\nmodel.fit(X, y, epochs=150, batch_size=10, verbose=0)\n# evaluate the keras model\n_, accuracy = model.evaluate(X, y, verbose=0)\n...<\/pre>\n<p style=\"text-align: justify;\">\u062a\u0648\u062c\u0647: \u0646\u062a\u0627\u06cc\u062c \u0634\u0645\u0627 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u0627\u0647\u06cc\u062a \u062a\u0635\u0627\u062f\u0641\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627 \u0631\u0648\u0634 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u060c \u06cc\u0627 \u062a\u0641\u0627\u0648\u062a \u062f\u0631 \u062f\u0642\u062a \u0639\u062f\u062f\u06cc \u0645\u062a\u0641\u0627\u0648\u062a \u0628\u0627\u0634\u062f. \u0686\u0646\u062f \u0628\u0627\u0631 \u0627\u062c\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0631\u0627 \u062f\u0631 \u0646\u0638\u0631 \u0628\u06af\u06cc\u0631\u06cc\u062f \u0648 \u0646\u062a\u06cc\u062c\u0647 \u0645\u062a\u0648\u0633\u0637 \u0631\u0627 \u0645\u0642\u0627\u06cc\u0633\u0647 \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0686\u0647 \u0646\u062a\u06cc\u062c\u0647 \u0627\u06cc \u06af\u0631\u0641\u062a\u06cc\u062f\u061f<\/p>\n<p style=\"text-align: justify;\">\u0646\u062a\u0627\u06cc\u062c \u062e\u0648\u062f \u0631\u0627 \u062f\u0631 \u0646\u0638\u0631\u0627\u062a \u0627\u0631\u0633\u0627\u0644 \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0634\u0628\u06a9\u0647 \u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062a\u0635\u0627\u062f\u0641\u06cc \u0627\u0633\u062a \u060c \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0639\u0646\u06cc \u06a9\u0647 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0645\u0634\u0627\u0628\u0647 \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u0634\u0627\u0628\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0647\u0631 \u0628\u0627\u0631 \u06a9\u0647 \u06a9\u062f \u0627\u062c\u0631\u0627 \u0645\u06cc \u0634\u0648\u062f \u060c \u0645\u062f\u0644 \u062f\u06cc\u06af\u0631\u06cc \u0631\u0627 \u0628\u0627 \u0645\u0647\u0627\u0631\u062a \u0645\u062a\u0641\u0627\u0648\u062a \u062a\u0631\u0628\u06cc\u062a \u06a9\u0646\u062f. \u0627\u06cc\u0646 \u06cc\u06a9 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0633\u062a \u060c \u0646\u0647 \u06cc\u06a9 \u0627\u0634\u06a9\u0627\u0644.<\/p>\n<p style=\"text-align: justify;\">\u0648\u0627\u0631\u06cc\u0627\u0646\u0633 \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062f\u0644 \u0628\u062f\u06cc\u0646 \u0645\u0639\u0646\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0628\u0631\u0627\u06cc \u0628\u0647 \u062f\u0633\u062a \u0622\u0648\u0631\u062f\u0646 \u062a\u0642\u0631\u06cc\u0628\u06cc \u0645\u0646\u0627\u0633\u0628 \u0627\u0632 \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062f\u0644 \u0634\u0645\u0627 \u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0644\u0627\u0632\u0645 \u0628\u0627\u0634\u062f \u0686\u0646\u062f\u06cc\u0646 \u0628\u0627\u0631 \u0622\u0646 \u0631\u0627 \u0645\u062a\u0646\u0627\u0633\u0628 \u06a9\u0646\u06cc\u062f \u0648 \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u0646\u0645\u0631\u0627\u062a \u062f\u0642\u062a \u0631\u0627 \u0645\u062d\u0627\u0633\u0628\u0647 \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644 \u060c \u062f\u0631 \u0632\u06cc\u0631 \u06f5 \u0628\u0627\u0631 \u0646\u0645\u0631\u0647 \u062f\u0642\u062a \u062f\u0631 \u0627\u062c\u0631\u0627\u06cc \u0645\u062c\u062f\u062f \u0645\u062b\u0627\u0644 \u0622\u0648\u0631\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">Accuracy: 75.00\nAccuracy: 77.73\nAccuracy: 77.60\nAccuracy: 78.12\nAccuracy: 76.17<\/pre>\n<p style=\"text-align: justify;\">\u0645\u06cc \u0628\u06cc\u0646\u06cc\u0645 \u06a9\u0647 \u062a\u0645\u0627\u0645 \u0646\u0645\u0631\u0627\u062a \u062f\u0642\u062a \u062f\u0631 \u062d\u062f\u0648\u062f \u06f7\u06f7\u066a \u0648 \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u06f7\u06f6\u066b\u06f9\u06f2\u06f4\u066a \u0627\u0633\u062a.<\/p>\n\n\n<h2 class=\"wp-block-heading\" id=\"h-7\"><span class=\"ez-toc-section\" id=\"%DB%B7-_%D9%BE%DB%8C%D8%B4_%D8%A8%DB%8C%D9%86%DB%8C_%D8%B1%D8%A7_%D8%A7%D9%86%D8%AC%D8%A7%D9%85_%D8%AF%D9%87%DB%8C%D8%AF\"><\/span><strong>\u06f7- \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc<\/strong> \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u062f<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0627\u0648\u0644\u06cc\u0646 \u0633\u0648\u0627\u0644 \u0627\u06cc\u0646 \u0627\u0633\u062a:<\/p>\n<p style=\"text-align: justify;\">\u0628\u0639\u062f \u0627\u0632 \u0627\u06cc\u0646\u06a9\u0647 \u0645\u062f\u0644 \u062e\u0648\u062f \u0631\u0627 \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u062f\u0645 \u060c \u0686\u06af\u0648\u0646\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u0645 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062c\u062f\u06cc\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u0645\u061f<\/p>\n<p style=\"text-align: justify;\">\u0633\u0648\u0627\u0644 \u0639\u0627\u0644\u06cc \u0627\u0633\u062a<\/p>\n<p style=\"text-align: justify;\">\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0645\u062b\u0627\u0644 \u0641\u0648\u0642 \u0631\u0627 \u062a\u0637\u0628\u06cc\u0642 \u062f\u0647\u06cc\u0645 \u0648 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645 \u060c \u0648\u0627\u0646\u0645\u0648\u062f \u06a9\u0646\u06cc\u0645 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062c\u062f\u06cc\u062f\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0642\u0628\u0644\u0627\u064b \u0646\u062f\u06cc\u062f\u0647 \u0627\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0627\u0646\u062c\u0627\u0645 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0647\u0627 \u0628\u0647 \u0622\u0633\u0627\u0646\u06cc \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u062a\u0627\u0628\u0639 predict() \u062f\u0631 \u0645\u062f\u0644 \u0622\u0633\u0627\u0646 \u0627\u0633\u062a. \u0645\u0627 \u062f\u0631 \u0644\u0627\u06cc\u0647 \u062e\u0631\u0648\u062c\u06cc \u0627\u0632 \u06cc\u06a9 \u062a\u0627\u0628\u0639 \u0641\u0639\u0627\u0644 \u0633\u0627\u0632\u06cc sigmoid \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0647\u0627 \u062f\u0631 \u0645\u062d\u062f\u0648\u062f\u0647 \u06f0 \u062a\u0627 \u06f1 \u0627\u062d\u062a\u0645\u0627\u0644 \u062f\u0627\u0631\u062f. \u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0627 \u06af\u0631\u062f \u06a9\u0631\u062f\u0646 \u0622\u0646 \u0647\u0627 \u060c \u0622\u0646 \u0647\u0627 \u0631\u0627 \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u0628\u0647 \u06cc\u06a9 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0628\u0627\u06cc\u0646\u0631\u06cc \u0648\u0627\u0636\u062d \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u0645\u062b\u0644\u0627<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# make probability predictions with the model\npredictions = model.predict(X)\n# round predictions \nrounded = [round(x[0]) for x in predictions]<\/pre>\n<p style=\"text-align: justify;\">\u0645\u062a\u0646\u0627\u0648\u0628\u0627\u064b \u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u062a\u0627\u0628\u0639 predict_classes () \u0631\u0627 \u062f\u0631 \u0645\u062f\u0644 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u0645\u0633\u062a\u0642\u06cc\u0645\u0627\u064b \u06a9\u0644\u0627\u0633 \u0647\u0627\u06cc \u0648\u0627\u0636\u062d \u0631\u0627 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u062f \u060c \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">...\n# make class predictions with the model\npredictions = model.predict_classes(X)<\/pre>\n<p style=\"text-align: justify;\">\u0645\u062b\u0627\u0644 \u06a9\u0627\u0645\u0644 \u0632\u06cc\u0631 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0628\u0631\u0627\u06cc \u0647\u0631 \u0645\u062b\u0627\u0644 \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u060c \u0633\u067e\u0633 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u060c \u06a9\u0644\u0627\u0633 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u0648 \u06a9\u0644\u0627\u0633 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u0631\u0627 \u0628\u0631\u0627\u06cc \u06f5 \u0645\u062b\u0627\u0644 \u0627\u0648\u0644 \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0686\u0627\u067e \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># first neural network with keras make predictions\nfrom numpy import loadtxt\nfrom keras.models import Sequential\nfrom keras.layers import Dense\n# load the dataset\ndataset = loadtxt('pima-indians-diabetes.csv', delimiter=',')\n# split into input (X) and output (y) variables\nX = dataset[:,0:8]\ny = dataset[:,8]\n# define the keras model\nmodel = Sequential()\nmodel.add(Dense(12, input_dim=8, activation='relu'))\nmodel.add(Dense(8, activation='relu'))\nmodel.add(Dense(1, activation='sigmoid'))\n# compile the keras model\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n# fit the keras model on the dataset\nmodel.fit(X, y, epochs=150, batch_size=10, verbose=0)\n# make class predictions with the model\npredictions = model.predict_classes(X)\n# summarize the first 5 cases\nfor i in range(5):\n  print('%s =&gt; %d (expected %d)' % (X[i].tolist(), predictions[i], y[i]))<\/pre>\n<p style=\"text-align: justify;\">\u0627\u062c\u0631\u0627\u06cc \u0645\u062b\u0627\u0644 \u0645\u0627\u0646\u0646\u062f \u0642\u0628\u0644 \u0646\u0648\u0627\u0631 \u067e\u06cc\u0634\u0631\u0641\u062a \u0631\u0627 \u0646\u0634\u0627\u0646 \u0646\u0645\u06cc \u062f\u0647\u062f \u0632\u06cc\u0631\u0627 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 verbos \u0631\u0627 \u0631\u0648\u06cc \u06f0 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0627\u06cc\u0645.<\/p>\n<p style=\"text-align: justify;\">\u067e\u0633 \u0627\u0632 \u0645\u0646\u0627\u0633\u0628 \u0628\u0648\u062f\u0646 \u0645\u062f\u0644 \u060c \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0647\u0627\u06cc\u06cc \u0628\u0631\u0627\u06cc \u0647\u0645\u0647 \u0645\u062b\u0627\u0644 \u0647\u0627\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc \u0634\u0648\u062f \u0648 \u0633\u0637\u0631\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0648 \u0645\u0642\u062f\u0627\u0631 \u06a9\u0644\u0627\u0633 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u0628\u0631\u0627\u06cc \u06f5 \u0645\u062b\u0627\u0644 \u0627\u0648\u0644 \u0686\u0627\u067e \u0645\u06cc \u0634\u0648\u0646\u062f \u0648 \u0628\u0627 \u0645\u0642\u062f\u0627\u0631 \u06a9\u0644\u0627\u0633 \u0645\u0648\u0631\u062f \u0627\u0646\u062a\u0638\u0627\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0645\u06cc \u0628\u06cc\u0646\u06cc\u0645 \u06a9\u0647 \u0627\u06a9\u062b\u0631 \u0631\u062f\u06cc\u0641 \u0647\u0627 \u0628\u0647 \u062f\u0631\u0633\u062a\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u0627\u0646\u062f. \u062f\u0631 \u062d\u0642\u06cc\u0642\u062a \u060c \u0645\u0627 \u0627\u0646\u062a\u0638\u0627\u0631 \u062f\u0627\u0631\u06cc\u0645 \u06a9\u0647 \u062d\u062f\u0648\u062f \u06f7\u06f6\u066b\u06f9\u066a \u0627\u0632 \u0631\u062f\u06cc\u0641 \u0647\u0627 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0639\u0645\u0644\u06a9\u0631\u062f \u062a\u062e\u0645\u06cc\u0646\u06cc \u0645\u0627 \u062f\u0631 \u0645\u062f\u0644 \u0642\u0628\u0644\u06cc \u060c \u0628\u0647 \u062f\u0631\u0633\u062a\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u0648\u0646\u062f.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">[\u06f6\u066b\u06f0, \u06f1\u06f4\u06f8\u066b\u06f0, \u06f7\u06f2\u066b\u06f0, \u06f3\u06f5\u066b\u06f0, \u06f0\u066b\u06f0, \u06f3\u06f3\u066b\u06f6, \u06f0\u066b\u06f6\u06f2\u06f7, \u06f5\u06f0\u066b\u06f0] =&gt; 0 (expected 1)\n[\u06f1\u066b\u06f0, \u06f8\u06f5\u066b\u06f0, \u06f6\u06f6\u066b\u06f0, \u06f2\u06f9\u066b\u06f0, \u06f0\u066b\u06f0, \u06f2\u06f6\u066b\u06f6, \u06f0\u066b\u06f3\u06f5\u06f1, \u06f3\u06f1\u066b\u06f0] =&gt; 0 (expected 0)\n[\u06f8\u066b\u06f0, \u06f1\u06f8\u06f3\u066b\u06f0, \u06f6\u06f4\u066b\u06f0, \u06f0\u066b\u06f0, \u06f0\u066b\u06f0, \u06f2\u06f3\u066b\u06f3, \u06f0\u066b\u06f6\u06f7\u06f2, \u06f3\u06f2\u066b\u06f0] =&gt; 1 (expected 1)\n[\u06f1\u066b\u06f0, \u06f8\u06f9\u066b\u06f0, \u06f6\u06f6\u066b\u06f0, \u06f2\u06f3\u066b\u06f0, \u06f9\u06f4\u066b\u06f0, \u06f2\u06f8\u066b\u06f1, \u06f0\u066b\u06f1\u06f6\u06f7, \u06f2\u06f1\u066b\u06f0] =&gt; 0 (expected 0)\n[\u06f0\u066b\u06f0, \u06f1\u06f3\u06f7\u066b\u06f0, \u06f4\u06f0\u066b\u06f0, \u06f3\u06f5\u066b\u06f0, \u06f1\u06f6\u06f8\u066b\u06f0, \u06f4\u06f3\u066b\u06f1, \u06f2\u066b\u06f2\u06f8\u06f8, \u06f3\u06f3\u066b\u06f0] =&gt; 1 (expected 1)<\/pre>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%D8%AE%D9%84%D8%A7%D8%B5%D9%87_%D8%A2%D9%85%D9%88%D8%B2%D8%B4_%DA%A9%D8%B1%D8%A7%D8%B3\"><\/span><strong>\u062e\u0644\u0627\u0635\u0647 \u0622\u0645\u0648\u0632\u0634 \u06a9\u0631\u0627\u0633<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u062f\u0631 \u0627\u06cc\u0646 \u067e\u0633\u062a \u060c \u0634\u0645\u0627 \u06a9\u0634\u0641 \u06a9\u0631\u062f\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0627\u0648\u0644\u06cc\u0646 \u0645\u062f\u0644 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0642\u062f\u0631\u062a\u0645\u0646\u062f Keras Python \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u060c \u0634\u0645\u0627 \u0634\u0634 \u0645\u0631\u062d\u0644\u0647 \u0627\u0635\u0644\u06cc \u0631\u0627 \u062f\u0631 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 Keras \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u06cc\u0627 \u0645\u062f\u0644 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u06cc\u0627\u062f \u06af\u0631\u0641\u062a\u06cc\u062f \u060c \u0645\u0631\u0627\u062d\u0644 \u0634\u0627\u0645\u0644:<\/p>\n<ul style=\"text-align: justify;\">\n<li>\u0646\u062d\u0648\u0647 \u0628\u0627\u0631\u06af\u06cc\u0631\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627.<\/li>\n<li>\u0646\u062d\u0648\u0647 \u062a\u0639\u0631\u06cc\u0641 \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u062f\u0631 \u06a9\u0631\u0627\u0633.<\/li>\n<li>\u0646\u062d\u0648\u0647 \u062a\u062f\u0648\u06cc\u0646 \u0645\u062f\u0644 Keras \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0628\u0627\u0632\u062f\u0647 \u0639\u062f\u062f\u06cc \u06a9\u0627\u0631\u0622\u0645\u062f.<\/li>\n<li>\u0646\u062d\u0648\u0647 \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u0628\u0631 \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627.<\/li>\n<li>\u0646\u062d\u0648\u0647 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u062f\u0644 \u0628\u0631 \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627.<\/li>\n<li>\u0686\u06af\u0648\u0646\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0627 \u0645\u062f\u0644 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0631\u062f.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">\u0622\u06cc\u0627 \u062f\u0631 \u0645\u0648\u0631\u062f \u06a9\u0631\u0627\u0633 \u06cc\u0627 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0633\u0648\u0627\u0644\u06cc \u062f\u0627\u0631\u06cc\u062f\u061f<\/p>\n<p style=\"text-align: justify;\">\u0633\u0648\u0627\u0644 \u062e\u0648\u062f \u0631\u0627 \u062f\u0631 \u0646\u0638\u0631\u0627\u062a \u0645\u0637\u0631\u062d \u06a9\u0646\u06cc\u062f \u0648 \u0645\u0627 \u062a\u0645\u0627\u0645 \u062a\u0644\u0627\u0634 \u062e\u0648\u062f \u0631\u0627 \u0628\u0631\u0627\u06cc \u067e\u0627\u0633\u062e\u06af\u0648\u06cc\u06cc \u0627\u0646\u062c\u0627\u0645 \u062e\u0648\u0627\u0647\u0645 \u062f\u0627\u062f.<\/p>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%D9%85%D9%88%D8%A7%D8%B1%D8%AF_%D8%A7%D8%B6%D8%A7%D9%81%D9%87_%D8%A2%D9%85%D9%88%D8%B2%D8%B4_Keras\"><\/span><strong>\u0645\u0648\u0627\u0631\u062f \u0627\u0636\u0627\u0641\u0647 \u0622\u0645\u0648\u0632\u0634 Keras<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p style=\"text-align: justify;\">\u0622\u0641\u0631\u06cc\u0646 \u060c \u0634\u0645\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u06a9\u0631\u0627\u0633 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 \u0645\u0648\u0641\u0642\u06cc\u062a \u0627\u0648\u0644\u06cc\u0646 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u062e\u0648\u062f \u0631\u0627 \u062a\u0648\u0633\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u06cc\u062f.<\/p>\n<p style=\"text-align: justify;\">\u0627\u06cc\u0646 \u0628\u062e\u0634 \u0628\u0631\u062e\u06cc \u0627\u0632 \u0627\u0641\u0632\u0648\u0646\u0647 \u0647\u0627\u06cc \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0631\u0627 \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u062e\u0648\u0627\u0647\u06cc\u062f \u0622\u0646 \u0647\u0627 \u0631\u0627 \u06a9\u0627\u0648\u0634 \u06a9\u0646\u06cc\u062f.<\/p>\n<ul>\n<li style=\"text-align: justify;\"><strong>\u0645\u062f\u0644 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f.<\/strong> \u067e\u06cc\u06a9\u0631\u0628\u0646\u062f\u06cc \u0645\u062f\u0644 \u06cc\u0627 \u0631\u0648\u0646\u062f \u0622\u0645\u0648\u0632\u0634 \u0631\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0647\u06cc\u062f \u0648 \u0628\u0628\u06cc\u0646\u06cc\u062f \u0622\u06cc\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062f\u0644 \u0631\u0627 \u0628\u0647\u0628\u0648\u062f \u0628\u0628\u062e\u0634\u06cc\u062f \u060c \u062f\u0633\u062a\u06cc\u0627\u0628\u06cc \u0628\u0647 \u062f\u0642\u062a \u0628\u0647\u062a\u0631 \u0627\u0632 \u06f7\u06f6\u066a .<\/li>\n<li style=\"text-align: justify;\"><strong>\u0645\u062f\u0644 \u0631\u0627 \u0630\u062e\u06cc\u0631\u0647 \u06a9\u0646\u06cc\u062f.<\/strong> \u0622\u0645\u0648\u0632\u0634 \u0631\u0627 \u0628\u0647 \u0631\u0648\u0632 \u06a9\u0646\u06cc\u062f \u062a\u0627 \u0645\u062f\u0644 \u0631\u0627 \u062f\u0631 \u067e\u0631\u0648\u0646\u062f\u0647 \u0630\u062e\u06cc\u0631\u0647 \u06a9\u0646\u06cc\u062f \u060c \u0633\u067e\u0633 \u0628\u0639\u062f\u0627\u064b \u0622\u0646 \u0631\u0627 \u0628\u0627\u0631\u06af\u06cc\u0631\u06cc \u06a9\u0646\u06cc\u062f \u0648 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\"><strong>\u062e\u0644\u0627\u0635\u0647 \u0645\u062f\u0644.<\/strong> \u0628\u0631\u0627\u06cc \u062e\u0644\u0627\u0635\u0647 \u06a9\u0631\u062f\u0646 \u0645\u062f\u0644 \u0648 \u0627\u06cc\u062c\u0627\u062f \u06cc\u06a9 \u0637\u0631\u062d \u0627\u0632 \u0644\u0627\u06cc\u0647 \u0647\u0627\u06cc \u0645\u062f\u0644 \u060c \u0622\u0645\u0648\u0632\u0634 \u0631\u0627 \u0628\u0647 \u0631\u0648\u0632 \u06a9\u0646\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\"><strong>\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0648 \u0622\u0632\u0645\u0648\u0646 \u062c\u062f\u0627\u06af\u0627\u0646\u0647.<\/strong> \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u0634\u062f\u0647 \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u0622\u0645\u0648\u0632\u0634 \u0648 \u0622\u0632\u0645\u0648\u0646 \u062a\u0642\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u062f (\u0628\u0631 \u0627\u0633\u0627\u0633 \u0631\u062f\u06cc\u0641 \u0647\u0627 \u062a\u0642\u0633\u06cc\u0645 \u0634\u062f\u0647) \u0648 \u0627\u0632 \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u0648 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u06cc\u06af\u0631 \u0628\u0631\u0627\u06cc \u062a\u062e\u0645\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062f\u0644 \u0628\u0631 \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062c\u062f\u06cc\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\"><strong>\u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627\u06cc \u0645\u0646\u062d\u0646\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc.<\/strong> \u062a\u0627\u0628\u0639 fit () \u06cc\u06a9 \u0634\u06cc history \u062a\u0627\u0631\u06cc\u062e \u0631\u0627 \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f \u06a9\u0647 \u062e\u0644\u0627\u0635\u0647 \u0632\u06cc\u0627\u0646 \u0648 \u062f\u0642\u062a \u062f\u0631 \u067e\u0627\u06cc\u0627\u0646 \u0647\u0631 \u062f\u0648\u0631\u0647 \u0627\u0633\u062a. \u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627\u06cc \u062e\u0637\u06cc \u0627\u0632 \u0627\u06cc\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0646\u0627\u0645 \u0645\u0646\u062d\u0646\u06cc \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\"><strong>\u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062c\u062f\u06cc\u062f \u0628\u06cc\u0627\u0645\u0648\u0632\u06cc\u062f.<\/strong> \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062c\u062f\u0627\u0648\u0644\u06cc \u062c\u062f\u0627\u06af\u0627\u0646\u0647 \u0627\u06cc \u060c \u0634\u0627\u06cc\u062f \u0627\u0632 \u0645\u062e\u0632\u0646 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 UCI \u060c \u0622\u0645\u0648\u0632\u0634 \u0631\u0627 \u0628\u0647 \u0631\u0648\u0632 \u06a9\u0646\u06cc\u062f.<\/li>\n<li style=\"text-align: justify;\"><strong>\u0627\u0632 <\/strong><strong>API<\/strong><strong> \u0639\u0645\u0644\u06a9\u0631\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f.<\/strong> \u0622\u0645\u0648\u0632\u0634 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 Keras Functional API \u0628\u0631\u0627\u06cc \u062a\u0639\u0631\u06cc\u0641 \u0645\u062f\u0644 \u0631\u0627 \u0628\u0647 \u0631\u0648\u0632 \u06a9\u0646\u06cc\u062f.<\/li>\n<\/ul>\n<h4><strong>\u0628\u06cc\u0634\u062a\u0631 \u0628\u062e\u0648\u0627\u0646\u06cc\u062f :<\/strong><\/h4>\n\n\n<div class=\"wp-block-group has-vivid-green-cyan-color has-text-color\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<ul class=\"wp-block-yoast-seo-related-links\"><li><a href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/why-keras-leading-deep-learning-api\/\">\u0686\u0631\u0627 Keras \u060c API \u067e\u06cc\u0634\u0631\u0648 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0627\u0633\u062a\u061f<\/a><\/li><li><a href=\"https:\/\/shahaab-co.com\/mag\/edu\/tensorflow-intro\/\">\u0622\u0634\u0646\u0627\u06cc\u06cc \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648<\/a><\/li><li><a href=\"https:\/\/shahaab-co.com\/mag\/edu\/machine-vision\/license-plate-recognition-using-opencv-yolo-and-keras\/\">\u067e\u0631\u0648\u0698\u0647 \u062a\u0634\u062e\u06cc\u0635 \u067e\u0644\u0627\u06a9 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 OpenCV \u060c YOLO \u0648 Keras<\/a><\/li><li><a href=\"https:\/\/shahaab-co.com\/mag\/edu\/deep-learning\/deep-learning-simplified-what-is-neural-network-ep-2\/\">\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0647 \u0632\u0628\u0627\u0646 \u0633\u0627\u062f\u0647 : \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0686\u06cc\u0633\u062a &#8211; \u0642\u0633\u0645\u062a \u062f\u0648\u0645<\/a><\/li><li><a href=\"https:\/\/shahaab-co.com\/mag\/programming-tools\/get-started-with-imagenet-part-1\/\">\u06a9\u0627\u0631 \u0628\u0627 \u067e\u0627\u06cc\u06af\u0627\u0647 \u062f\u0627\u062f\u0647 ImageNet &#8211; \u0642\u0633\u0645\u062a \u0627\u0648\u0644<\/a><\/li><\/ul>\n\n\n\n<a href=\"#\" class=\"shortc-button small blue \">\u0645\u0646\u0628\u0639<\/a> <a href=\"https:\/\/machinelearningmastery.com\/tutorial-first-neural-network-python-keras\/\" target=\"_blank\" class=\"shortc-button small gray \" rel=\"noopener\">Machine Learning Mastery<\/a>\n<\/div><\/div>\n\n\n<div class=\"kk-star-ratings kksr-auto kksr-align-right kksr-valign-bottom\"\n    data-payload='{&quot;align&quot;:&quot;right&quot;,&quot;id&quot;:&quot;10626&quot;,&quot;slug&quot;:&quot;default&quot;,&quot;valign&quot;:&quot;bottom&quot;,&quot;ignore&quot;:&quot;&quot;,&quot;reference&quot;:&quot;auto&quot;,&quot;class&quot;:&quot;&quot;,&quot;count&quot;:&quot;0&quot;,&quot;legendonly&quot;:&quot;&quot;,&quot;readonly&quot;:&quot;&quot;,&quot;score&quot;:&quot;0&quot;,&quot;starsonly&quot;:&quot;&quot;,&quot;best&quot;:&quot;5&quot;,&quot;gap&quot;:&quot;5&quot;,&quot;greet&quot;:&quot;\u0627\u0645\u062a\u06cc\u0627\u0632 \u062f\u0647\u06cc\u062f!&quot;,&quot;legend&quot;:&quot;0\\\/5 - (0 \u0627\u0645\u062a\u06cc\u0627\u0632)&quot;,&quot;size&quot;:&quot;24&quot;,&quot;title&quot;:&quot;\u067e\u0631\u0648\u0698\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 Keras \u0628\u0647 \u0635\u0648\u0631\u062a \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645&quot;,&quot;width&quot;:&quot;0&quot;,&quot;_legend&quot;:&quot;{score}\\\/{best} - ({count} \u0627\u0645\u062a\u06cc\u0627\u0632)&quot;,&quot;font_factor&quot;:&quot;1.25&quot;}'>\n            \n<div class=\"kksr-stars\">\n    \n<div class=\"kksr-stars-inactive\">\n            <div class=\"kksr-star\" data-star=\"1\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"2\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"3\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"4\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"5\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n    <\/div>\n    \n<div class=\"kksr-stars-active\" style=\"width: 0px;\">\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n                \n\n<div class=\"kksr-legend\" style=\"font-size: 19.2px;\">\n            <span class=\"kksr-muted\">\u0627\u0645\u062a\u06cc\u0627\u0632 \u062f\u0647\u06cc\u062f!<\/span>\n    <\/div>\n    <\/div>\n","protected":false},"excerpt":{"rendered":"<p>Keras \u06cc\u06a9 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0646\u0628\u0639 \u0628\u0627\u0632 \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0648 \u0628\u0627 \u06a9\u0627\u0631\u0628\u0631\u062f \u0622\u0633\u0627\u0646 \u0628\u0631\u0627\u06cc \u062a\u0648\u0633\u0639\u0647 \u0648 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0627\u0633\u062a. \u06a9\u0631\u0627\u0633\u060c \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647\u200c\u0647\u0627\u06cc \u0645\u062d\u0627\u0633\u0628\u0627\u062a\u06cc \u0639\u062f\u062f\u06cc Theano \u0648 TensorFlow \u0631\u0627 \u06a9\u0627\u0631\u0622\u0645\u062f \u06a9\u0631\u062f\u0647 \u0648 \u0628\u0647 \u0634\u0645\u0627 \u0627\u06cc\u0646 \u00a0\u0627\u0645\u06a9\u0627\u0646 \u0631\u0627 \u0645\u06cc\u200c\u062f\u0647\u062f \u06a9\u0647 \u0641\u0642\u0637 \u062f\u0631 \u0686\u0646\u062f \u062e\u0637 \u06a9\u062f\u060c \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u0648 \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u062f. \u062f\u0631 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u060c \u0634\u0645\u0627 &hellip;<\/p>\n","protected":false},"author":7,"featured_media":10636,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","footnotes":""},"categories":[19,18],"tags":[84,147,86],"class_list":["post-10626","post","type-post","status-publish","format-standard","has-post-thumbnail","","category-deep-learning","category-edu","tag-84","tag-147","tag-86"],"_links":{"self":[{"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/posts\/10626","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/comments?post=10626"}],"version-history":[{"count":1,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/posts\/10626\/revisions"}],"predecessor-version":[{"id":16212,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/posts\/10626\/revisions\/16212"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/media\/10636"}],"wp:attachment":[{"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/media?parent=10626"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/categories?post=10626"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/shahaab-co.com\/mag\/wp-json\/wp\/v2\/tags?post=10626"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}