{"id":102670,"date":"2025-05-27T19:49:21","date_gmt":"2025-05-27T19:49:21","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/%d8%af%d8%a7%d9%86%d9%84%d9%88%d8%af-%d8%af%d9%88%d8%b1%d9%87-udemy-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d8%b9%d9%85%db%8c%d9%82-%d8%a8%d8%a7-%d8%b4%d8%a8%da%a9%d9%87%d9%87%d8%a7\/"},"modified":"2025-05-27T19:49:25","modified_gmt":"2025-05-27T19:49:25","slug":"%d8%af%d8%a7%d9%86%d9%84%d9%88%d8%af-%d8%af%d9%88%d8%b1%d9%87-udemy-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d8%b9%d9%85%db%8c%d9%82-%d8%a8%d8%a7-%d8%b4%d8%a8%da%a9%d9%87%d9%87%d8%a7","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%af%d8%a7%d9%86%d9%84%d9%88%d8%af-%d8%af%d9%88%d8%b1%d9%87-udemy-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d8%b9%d9%85%db%8c%d9%82-%d8%a8%d8%a7-%d8%b4%d8%a8%da%a9%d9%87%d9%87%d8%a7\/","title":{"rendered":"\u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 Udemy: \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646"},"content":{"rendered":"\n\n\n\n\n\n
\u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/th>\n\u062f\u0627\u0646\u0644\u0648\u062f Udemy – Deep Learning: Recurrent Neural Networks in Python<\/td>\n<\/tr>\n
\u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc<\/th>\n\u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 Udemy: \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646<\/th>\n\u0627\u0646\u06af\u0644\u06cc\u0633\u06cc \u0628\u0627 \u0632\u06cc\u0631\u0646\u0648\u06cc\u0633 \u0641\u0627\u0631\u0633\u06cc<\/td>\n<\/tr>\n
\u0646\u0648\u0639 \u0645\u062d\u0635\u0648\u0644<\/th>\n\u0622\u0645\u0648\u0632\u0634 \u0648\u06cc\u062f\u06cc\u0648\u06cc\u06cc<\/td>\n<\/tr>\n
\u0646\u062d\u0648\u0647 \u062a\u062d\u0648\u06cc\u0644<\/th>\n\u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0627\u0646\u0644\u0648\u062f\u06cc<\/td>\n<\/tr>\n<\/table>\n
\r\n \u062a\u0648\u062c\u0647 \u0645\u0647\u0645:<\/strong>\r\n

\r\n \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u062f\u0627\u0646\u0644\u0648\u062f\u06cc<\/span> \u0628\u0648\u062f\u0647 \u0648 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627 \u0632\u06cc\u0631\u0646\u0648\u06cc\u0633 \u0641\u0627\u0631\u0633\u06cc<\/span> \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc\u200c\u06af\u0631\u062f\u062f.\r\n <\/p>\r\n

\r\n \u062d\u062f\u0627\u06a9\u062b\u0631 \u062a\u0627 \u06f2\u06f4 \u0633\u0627\u0639\u062a \u067e\u0633 \u0627\u0632 \u0633\u0641\u0627\u0631\u0634<\/strong>\u060c \u0644\u06cc\u0646\u06a9 \u0627\u062e\u062a\u0635\u0627\u0635\u06cc \u062f\u0648\u0631\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u0633\u0627\u062e\u062a\u0647 \u0648 \u062c\u0647\u062a \u062f\u0627\u0646\u0644\u0648\u062f \u0627\u0631\u0633\u0627\u0644 \u062e\u0648\u0627\u0647\u062f \u0634\u062f.\r\n <\/p>\r\n

\r\n \u062c\u0647\u062a \u067e\u06cc\u06af\u06cc\u0631\u06cc \u0633\u0641\u0627\u0631\u0634\u060c \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0648\u0627\u062a\u0633\u200c\u0627\u067e \u0628\u0627 \u0634\u0645\u0627\u0631\u0647 09395106248<\/strong> \u06cc\u0627 \u0622\u06cc\u062f\u06cc \u062a\u0644\u06af\u0631\u0627\u0645\u06cc @ma_limbs<\/strong> \u062f\u0631 \u062a\u0645\u0627\u0633 \u0628\u0627\u0634\u06cc\u062f.\r\n <\/p>\r\n<\/div>\r\n\r\n\n

\n

\u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 Udemy: \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646<\/h1>\n

\u0645\u0639\u0631\u0641\u06cc \u062f\u0648\u0631\u0647<\/h2>\n
\n

\u062f\u0648\u0631\u0647 Deep Learning: Recurrent Neural Networks in Python<\/span> \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u062d\u0628\u0648\u0628\u200c\u062a\u0631\u06cc\u0646 \u062f\u0648\u0631\u0647\u200c\u0647\u0627\u06cc Udemy \u0627\u0633\u062a \u06a9\u0647 \u0628\u0631 \u0645\u0641\u0627\u0647\u06cc\u0645 \u0648 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc (RNN) \u0628\u0627 \u0632\u0628\u0627\u0646 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0645\u062a\u0645\u0631\u06a9\u0632 \u0627\u0633\u062a. \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0628\u0631\u0627\u06cc \u062f\u0627\u0646\u0634\u062c\u0648\u06cc\u0627\u0646\u060c \u067e\u0698\u0648\u0647\u0634\u06af\u0631\u0627\u0646 \u0648 \u0645\u0647\u0646\u062f\u0633\u0627\u0646\u06cc \u0637\u0631\u0627\u062d\u06cc \u0634\u062f\u0647 \u06a9\u0647 \u0642\u0635\u062f \u062f\u0627\u0631\u0646\u062f \u062f\u0631 \u0632\u0645\u06cc\u0646\u0647 \u067e\u0631\u062f\u0627\u0632\u0634 \u062a\u0648\u0627\u0644\u06cc\u200c\u0647\u0627\u060c \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc \u0648 \u0633\u0631\u06cc\u200c\u0647\u0627\u06cc \u0632\u0645\u0627\u0646\u06cc \u062a\u062c\u0631\u0628\u0647 \u06a9\u0633\u0628 \u06a9\u0646\u0646\u062f. \u0645\u062f\u0631\u0633 \u062f\u0648\u0631\u0647 \u0628\u0627 \u0631\u0648\u06cc\u06a9\u0631\u062f\u06cc \u067e\u0631\u0648\u0698\u0647\u200c\u0645\u062d\u0648\u0631 \u0648 \u0639\u0645\u0644\u06cc\u060c \u0627\u0632 \u0645\u0641\u0627\u0647\u06cc\u0645 \u067e\u0627\u06cc\u0647 \u062a\u0627 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u0631\u0627 \u067e\u0648\u0634\u0634 \u0645\u06cc\u200c\u062f\u0647\u062f.<\/p>\n<\/div>\n

\u0686\u0647 \u0686\u06cc\u0632\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0622\u0645\u0648\u062e\u062a\u061f<\/h2>\n
\n
    \n
  • \u062f\u0631\u06a9 \u0645\u0639\u0645\u0627\u0631\u06cc\u200c\u0647\u0627\u06cc \u067e\u0627\u06cc\u0647 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc (RNN) \u0648 \u0646\u062d\u0648\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0622\u0646\u200c\u0647\u0627.<\/li>\n
  • \u0628\u0631\u0631\u0633\u06cc \u0648 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0627\u0646\u0648\u0627\u0639 \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u0645\u062b\u0644 LSTM<\/span> \u0648 GRU<\/span>.<\/li>\n
  • \u06a9\u0627\u0631 \u0628\u0627 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647\u200c\u0647\u0627\u06cc \u0645\u062d\u0628\u0648\u0628 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0645\u0627\u0646\u0646\u062f TensorFlow<\/code> \u0648 Keras<\/code> \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u0648 \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644\u200c\u0647\u0627.<\/li>\n
  • \u067e\u0631\u062f\u0627\u0632\u0634 \u0648 \u067e\u06cc\u0634\u200c\u067e\u0631\u062f\u0627\u0632\u0634 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u062a\u0646\u06cc \u0648 \u0633\u0631\u06cc\u200c\u0647\u0627\u06cc \u0632\u0645\u0627\u0646\u06cc.<\/li>\n
  • \u0627\u0641\u0632\u0627\u06cc\u0634 \u06a9\u0627\u0631\u0627\u06cc\u06cc \u0645\u062f\u0644 \u0628\u0627 \u062a\u06a9\u0646\u06cc\u06a9\u200c\u0647\u0627\u06cc \u062a\u0646\u0638\u06cc\u0645 \u0627\u0628\u0631\u067e\u0627\u0631\u0627\u0645\u062a\u0631\u060c \u062c\u0644\u0648\u06af\u06cc\u0631\u06cc \u0627\u0632 overfitting<\/span> \u0648 \u0628\u0647\u0628\u0648\u062f \u0647\u0645\u06af\u0631\u0627\u06cc\u06cc.<\/li>\n
  • \u0627\u06cc\u062c\u0627\u062f \u067e\u0631\u0648\u0698\u0647\u200c\u0647\u0627\u06cc \u0639\u0645\u0644\u06cc \u0634\u0627\u0645\u0644 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0642\u06cc\u0645\u062a \u0633\u0647\u0627\u0645\u060c \u062a\u0648\u0644\u06cc\u062f \u0645\u062a\u0646 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a.<\/li>\n<\/ul>\n<\/div>\n

    \u0645\u0632\u0627\u06cc\u0627\u06cc \u0634\u0631\u06a9\u062a \u062f\u0631 \u062f\u0648\u0631\u0647<\/h2>\n
    \n
      \n
    • \u062f\u0633\u062a\u0631\u0633\u06cc \u0645\u0627\u062f\u0627\u0645\u200c\u0627\u0644\u0639\u0645\u0631 \u0628\u0647 \u0645\u062d\u062a\u0648\u0627 \u0648 \u0628\u0631\u0648\u0632\u0631\u0633\u0627\u0646\u06cc\u200c\u0647\u0627\u06cc \u0631\u0627\u06cc\u06af\u0627\u0646.<\/li>\n
    • \u062a\u0645\u0631\u06cc\u0646\u200c\u0647\u0627\u06cc \u06a9\u062f\u0646\u0648\u06cc\u0633\u06cc \u062a\u0639\u0627\u0645\u0644\u06cc \u0648 \u067e\u0631\u0648\u0698\u0647\u200c\u0647\u0627\u06cc \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645.<\/li>\n
    • \u06af\u0631\u0648\u0647 \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0648 \u062a\u0639\u0627\u0645\u0644 \u0628\u0627 \u0633\u0627\u06cc\u0631 \u0641\u0631\u0627\u06af\u06cc\u0631\u0627\u0646 \u062f\u0631 \u0627\u0646\u062c\u0645\u0646 \u062f\u0648\u0631\u0647.<\/li>\n
    • \u0645\u062f\u0631\u06a9 \u067e\u0627\u06cc\u0627\u0646 \u062f\u0648\u0631\u0647 \u0645\u0639\u062a\u0628\u0631 \u0627\u0632 Udemy \u0628\u0631\u0627\u06cc \u062a\u0642\u0648\u06cc\u062a \u0631\u0632\u0648\u0645\u0647 \u0648 \u067e\u0631\u0648\u0641\u0627\u06cc\u0644 \u0644\u06cc\u0646\u06a9\u062f\u06cc\u0646.<\/li>\n
    • \u0627\u06cc\u062c\u0627\u062f \u0646\u0645\u0648\u0646\u0647\u200c\u06a9\u0627\u0631\u0647\u0627\u06cc \u0648\u0627\u0642\u0639\u06cc \u062c\u0647\u062a \u0627\u0631\u0627\u0626\u0647 \u062f\u0631 \u0645\u0635\u0627\u062d\u0628\u0647\u200c\u0647\u0627\u06cc \u0634\u063a\u0644\u06cc.<\/li>\n<\/ul>\n<\/div>\n

      \u067e\u06cc\u0634\u200c\u0646\u06cc\u0627\u0632\u0647\u0627<\/h2>\n
      \n
        \n
      • \u0622\u0634\u0646\u0627\u06cc\u06cc \u0627\u0648\u0644\u06cc\u0647 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 (\u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u060c \u062d\u0644\u0642\u0647\u060c \u062a\u0648\u0627\u0628\u0639).<\/li>\n
      • \u062f\u0631\u06a9 \u0645\u0641\u0627\u0647\u06cc\u0645 \u067e\u0627\u06cc\u0647\u200c\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 (\u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc\u060c \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645).<\/li>\n
      • \u0622\u0634\u0646\u0627\u06cc\u06cc \u0645\u062e\u062a\u0635\u0631 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u067e\u0631\u0633\u067e\u062a\u0631\u0648\u0646 \u0686\u0646\u062f\u0644\u0627\u06cc\u0647 (MLP) \u0627\u0631\u0632\u0634\u0645\u0646\u062f \u0627\u0633\u062a.<\/li>\n
      • \u0646\u0635\u0628 Python 3.6+ \u0648 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647\u200c\u0647\u0627\u06cc TensorFlow 2.x<\/code> \u0648 Keras<\/code>.<\/li>\n<\/ul>\n<\/div>\n

        \u0633\u0627\u062e\u062a\u0627\u0631 \u0648 \u0628\u062e\u0634\u200c\u0647\u0627\u06cc \u062f\u0648\u0631\u0647<\/h2>\n
        \n
          \n
        • \n \u0645\u0642\u062f\u0645\u0647 \u0648 \u0646\u0635\u0628 \u0645\u062d\u06cc\u0637:<\/strong> \u0631\u0627\u0647\u200c\u0627\u0646\u062f\u0627\u0632\u06cc \u0645\u062d\u06cc\u0637 \u06a9\u0627\u0631\u06cc\u060c \u0622\u0634\u0646\u0627\u06cc\u06cc \u0628\u0627 \u062f\u0641\u062a\u0631\u0686\u0647\u200c\u0647\u0627\u06cc Jupyter \u0648 \u0628\u0631\u0631\u0633\u06cc \u0633\u0627\u062e\u062a\u0627\u0631 \u067e\u0631\u0648\u0698\u0647.\n <\/li>\n
        • \n \u0645\u0628\u0627\u0646\u06cc RNN:<\/strong> \u0622\u0634\u0646\u0627\u06cc\u06cc \u0628\u0627 \u0633\u0627\u062e\u062a\u0627\u0631 \u062d\u0644\u0642\u0648\u06cc\u060c \u0641\u0631\u0645\u0648\u0644\u200c\u0647\u0627\u06cc \u067e\u0633\u200c\u0627\u0646\u062a\u0634\u0627\u0631 \u0632\u0645\u0627\u0646-\u0628\u0647\u200c\u0639\u0642\u0628 (BPTT<\/em>) \u0648 \u0645\u0634\u06a9\u0644\u0627\u062a \u0646\u0627\u067e\u062f\u06cc\u062f \u0634\u062f\u0646\/\u0641\u0631\u0627\u0648\u0627\u0646\u06cc \u06af\u0631\u0627\u062f\u06cc\u0627\u0646.\n <\/li>\n
        • \n \u0645\u0639\u0645\u0627\u0631\u06cc LSTM:<\/strong> \u0645\u0639\u0631\u0641\u06cc \u0633\u0644\u0648\u0644\u200c\u0647\u0627\u06cc \u062d\u0627\u0641\u0638\u0647\u060c \u062f\u0631\u0648\u0627\u0632\u0647\u200c\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u060c \u062e\u0631\u0648\u062c \u0648 \u0641\u0631\u0627\u0645\u0648\u0634\u06cc \u0648 \u0646\u062d\u0648\u0647 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0622\u0646 \u062f\u0631 Keras.\n <\/li>\n
        • \n \u0645\u0639\u0645\u0627\u0631\u06cc GRU:<\/strong> \u0633\u0627\u062e\u062a\u0627\u0631\u06cc \u0633\u0627\u062f\u0647\u200c\u062a\u0631 \u0646\u0633\u0628\u062a \u0628\u0647 LSTM \u0648 \u0646\u062d\u0648\u0647 \u0628\u0647\u0628\u0648\u062f \u0633\u0631\u0639\u062a \u0622\u0645\u0648\u0632\u0634.\n <\/li>\n
        • \n \u067e\u0631\u062f\u0627\u0632\u0634 \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc (NLP):<\/strong> \u062a\u0648\u06a9\u0646\u200c\u0633\u0627\u0632\u06cc\u060c \u062a\u0639\u0628\u06cc\u0647 \u06a9\u0644\u0645\u0627\u062a (word embedding<\/em>) \u0648 \u0645\u062f\u0644\u200c\u0633\u0627\u0632\u06cc \u0633\u0644\u0633\u0644\u0647\u200c\u0627\u06cc.\n <\/li>\n
        • \n \u0633\u0631\u06cc\u200c\u0647\u0627\u06cc \u0632\u0645\u0627\u0646\u06cc:<\/strong> \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u0627\u0644\u06cc\u060c \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u0645\u062a\u062d\u0631\u06a9 \u0648 \u0627\u0639\u062a\u0628\u0627\u0631\u0633\u0646\u062c\u06cc \u0645\u062f\u0644.\n <\/li>\n
        • \n \u062a\u062e\u0635\u06cc\u0635 \u062a\u0648\u062c\u0647 (Attention<\/em>):<\/strong> \u0645\u0641\u0627\u0647\u06cc\u0645 \u067e\u0627\u06cc\u0647 \u062a\u0648\u062c\u0647\u200c\u0645\u062d\u0648\u0631 \u0648 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u062f\u0631 \u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc.\n <\/li>\n
        • \n \u067e\u0631\u0648\u0698\u0647\u200c\u0647\u0627\u06cc \u0646\u0647\u0627\u06cc\u06cc:<\/strong> \u062a\u0648\u0644\u06cc\u062f \u0645\u062a\u0646 \u0628\u0627 RNN\u060c \u0686\u062a\u200c\u0628\u0627\u062a \u0633\u0627\u062f\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a \u062a\u0648\u06cc\u06cc\u062a\u200c\u0647\u0627.\n <\/li>\n<\/ul>\n<\/div>\n

          \u0645\u062b\u0627\u0644\u200c\u0647\u0627\u06cc \u0639\u0645\u0644\u06cc<\/h2>\n
          \n

          \u062f\u0631 \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0645\u062b\u0627\u0644\u200c\u0647\u0627\u06cc \u0645\u062a\u0646\u0648\u0639\u06cc \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f. \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u0646\u0647\u060c \u062f\u0631 \u0628\u062e\u0634 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0642\u06cc\u0645\u062a \u0633\u0647\u0627\u0645 \u0627\u0632 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 pandas<\/code> \u0628\u0631\u0627\u06cc \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647\u200c\u0647\u0627 \u0648 \u0627\u0632 Keras<\/code> \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u0645\u062f\u0644 RNN \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645:<\/p>\n

          import numpy as np\nfrom keras.models import Sequential\nfrom keras.layers import LSTM, Dense\n\n# \u0622\u0645\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647\ndata = np.loadtxt('stock_prices.csv', delimiter=',')\nX, y = prepare_sequences(data, seq_length=50)\n\n# \u0633\u0627\u062e\u062a \u0645\u062f\u0644\nmodel = Sequential()\nmodel.add(LSTM(64, input_shape=(50, 1), return_sequences=False))\nmodel.add(Dense(1))\nmodel.compile(optimizer='adam', loss='mse')\n\n# \u0622\u0645\u0648\u0632\u0634\nmodel.fit(X, y, epochs=20, batch_size=32, validation_split=0.2)<\/code><\/pre>\n
          \u062f\u0631 \u0645\u062b\u0627\u0644 \u0628\u0627\u0644\u0627 \u0627\u0628\u062a\u062f\u0627 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0633\u0631\u06cc \u0632\u0645\u0627\u0646\u06cc \u0631\u0627 \u0628\u0647 \u062a\u0648\u0627\u0644\u06cc\u200c\u0647\u0627\u06cc\u06cc \u0628\u0627 \u0637\u0648\u0644 50 \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645\u060c \u0633\u067e\u0633 \u06cc\u06a9 \u0634\u0628\u06a9\u0647 LSTM \u0628\u0627 64 \u0648\u0627\u062d\u062f \u0645\u062e\u0641\u06cc \u0645\u06cc\u200c\u0633\u0627\u0632\u06cc\u0645 \u0648 \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a \u0645\u062f\u0644 \u0631\u0627 \u0622\u0645\u0648\u0632\u0634 \u0645\u06cc\u200c\u062f\u0647\u06cc\u0645.<\/p>\n<\/div>\n
          \u0646\u06a9\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc \u0648 \u0628\u0631\u062c\u0633\u062a\u0647<\/h2>\n
          \n
            \n
          • \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 stateful<\/span> RNN \u0628\u0631\u0627\u06cc \u0645\u062f\u0644\u200c\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631 \u0637\u0648\u0644\u0627\u0646\u06cc.<\/li>\n
          • \u062a\u0646\u0638\u06cc\u0645 \u0645\u0646\u0627\u0633\u0628 learning rate<\/span> \u0648 \u0646\u062d\u0648\u0647 \u06a9\u0627\u0647\u0634 \u062a\u062f\u0631\u06cc\u062c\u06cc \u0622\u0646 \u0628\u0627 callbacks<\/em>.<\/li>\n
          • \u062a\u0631\u06a9\u06cc\u0628 LSTM \u0648 GRU \u0628\u0631\u0627\u06cc \u062f\u0633\u062a\u06cc\u0627\u0628\u06cc \u0628\u0647 \u062a\u0639\u0627\u062f\u0644 \u0628\u06cc\u0646 \u062f\u0642\u062a \u0648 \u0633\u0631\u0639\u062a \u0622\u0645\u0648\u0632\u0634.<\/li>\n
          • \u0628\u0647\u200c\u06a9\u0627\u0631\u06af\u06cc\u0631\u06cc \u062a\u06a9\u0646\u06cc\u06a9\u200c\u0647\u0627\u06cc dropout<\/span> \u0648 regularization<\/span> \u0628\u0631\u0627\u06cc \u062c\u0644\u0648\u06af\u06cc\u0631\u06cc \u0627\u0632 \u0628\u06cc\u0634\u200c\u0628\u0631\u0627\u0632\u0634.<\/li>\n
          • \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u0627\u0639\u062a\u0628\u0627\u0631\u0633\u0646\u062c\u06cc \u0648 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u062f\u0644 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0646\u0645\u0648\u062f\u0627\u0631 loss<\/em> \u0648 accuracy<\/em> \u062f\u0631 \u0637\u0648\u0644 \u0622\u0645\u0648\u0632\u0634.<\/li>\n<\/ul>\n<\/div>\n<\/article>\n","protected":false},"excerpt":{"rendered":"
            \u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc \u062f\u0627\u0646\u0644\u0648\u062f Udemy – Deep Learning: Recurrent Neural Networks in Python \u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc \u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 […]<\/p>\n","protected":false},"featured_media":67493,"comment_status":"open","ping_status":"closed","template":"","meta":{"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}}},"product_cat":[1225],"product_tag":[227,1840,27454,19,1145,1435,1303,7558,1150,27455,27456,1128,7549,1120,2041,493,27453,2260,27451,7548,27452,261,674,267],"class_list":{"0":"post-102670","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-1225","7":"product_tag-ai","8":"product_tag-deep-learning","9":"product_tag-deep-learning-in-python","10":"product_tag-machine-learning","11":"product_tag-neural-networks","12":"product_tag-online-course","13":"product_tag-python","14":"product_tag-recurrent-neural-networks","15":"product_tag-rnn","16":"product_tag-rnn-in-python","17":"product_tag-sequence-modeling","18":"product_tag-udemy-course","19":"product_tag--rnn","20":"product_tag-1120","21":"product_tag-2041","22":"product_tag-493","23":"product_tag-27453","24":"product_tag---udemy","25":"product_tag-27451","26":"product_tag-7548","27":"product_tag-27452","28":"product_tag-261","29":"product_tag-674","30":"product_tag-267","31":"pmpro-has-access","32":"desktop-align-left","33":"tablet-align-left","34":"mobile-align-left","36":"first","37":"instock","38":"shipping-taxable","39":"purchasable","40":"product-type-variable"},"yoast_head":"\n\u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 Udemy: \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 - \u0641\u0631\u0648\u0634\u06af\u0627\u0647 \u0627\u06a9\u0633\u067e\u0631\u0633<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/express24.ir\/d\/product\/\u062f\u0627\u0646\u0644\u0648\u062f-\u062f\u0648\u0631\u0647-udemy-\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc-\u0639\u0645\u06cc\u0642-\u0628\u0627-\u0634\u0628\u06a9\u0647\u0647\u0627\/\" \/>\n<meta property=\"og:locale\" content=\"fa_IR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 Udemy: \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 - \u0641\u0631\u0648\u0634\u06af\u0627\u0647 \u0627\u06a9\u0633\u067e\u0631\u0633\" \/>\n<meta property=\"og:description\" content=\"\u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc \u062f\u0627\u0646\u0644\u0648\u062f Udemy – Deep Learning: Recurrent Neural Networks in Python \u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc \u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/express24.ir\/d\/product\/\u062f\u0627\u0646\u0644\u0648\u062f-\u062f\u0648\u0631\u0647-udemy-\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc-\u0639\u0645\u06cc\u0642-\u0628\u0627-\u0634\u0628\u06a9\u0647\u0647\u0627\/\" \/>\n<meta property=\"og:site_name\" content=\"\u0641\u0631\u0648\u0634\u06af\u0627\u0647 \u0627\u06a9\u0633\u067e\u0631\u0633\" \/>\n<meta property=\"article:modified_time\" content=\"2025-05-27T19:49:25+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/express24.ir\/d\/wp-content\/uploads\/2025\/05\/Express24_ir.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u0632\u0645\u0627\u0646 \u062a\u0642\u0631\u06cc\u0628\u06cc \u0628\u0631\u0627\u06cc \u062e\u0648\u0627\u0646\u062f\u0646\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 \u062f\u0642\u06cc\u0642\u0647\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/express24.ir\/d\/product\/%d8%af%d8%a7%d9%86%d9%84%d9%88%d8%af-%d8%af%d9%88%d8%b1%d9%87-udemy-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d8%b9%d9%85%db%8c%d9%82-%d8%a8%d8%a7-%d8%b4%d8%a8%da%a9%d9%87%d9%87%d8%a7\/\",\"url\":\"https:\/\/express24.ir\/d\/product\/%d8%af%d8%a7%d9%86%d9%84%d9%88%d8%af-%d8%af%d9%88%d8%b1%d9%87-udemy-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d8%b9%d9%85%db%8c%d9%82-%d8%a8%d8%a7-%d8%b4%d8%a8%da%a9%d9%87%d9%87%d8%a7\/\",\"name\":\"\u062f\u0627\u0646\u0644\u0648\u062f \u062f\u0648\u0631\u0647 Udemy: \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0627 \u0634\u0628\u06a9\u0647\u200c\u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0628\u0627\u0632\u06af\u0634\u062a\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 - 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