{"id":477370,"date":"2023-08-09T09:11:34","date_gmt":"2023-08-09T09:11:34","guid":{"rendered":""},"modified":"2023-09-05T11:14:34","modified_gmt":"2023-09-05T11:14:34","slug":"gradient-descent","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/in\/wiki\/gradient-descent\/","title":{"rendered":"\u0922\u0924\u0932\u093e \u0939\u0941\u0906 \u0935\u0902\u0936"},"content":{"rendered":"<p>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u090f\u0915 \u092a\u0941\u0928\u0930\u093e\u0935\u0943\u0924\u094d\u0924 \u0905\u0928\u0941\u0915\u0942\u0932\u0928 \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0925\u094d\u092e \u0939\u0948 \u091c\u093f\u0938\u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0905\u0915\u094d\u0938\u0930 \u0915\u093f\u0938\u0940 \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0938\u094d\u0925\u093e\u0928\u0940\u092f \u092f\u093e \u0935\u0948\u0936\u094d\u0935\u093f\u0915 \u0928\u094d\u092f\u0942\u0928\u0924\u092e 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\u0939\u0948\u0964<\/li>\n<li><strong>\u0905\u0928\u0941\u092e\u093e\u092a\u0915\u0924\u093e<\/strong>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f, \u0938\u094d\u091f\u094b\u091a\u0948\u0938\u094d\u091f\u093f\u0915 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0928\u093e\u092e\u0915 \u090f\u0915 \u092a\u094d\u0930\u0915\u093e\u0930 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 \u092c\u0939\u0941\u0924 \u092c\u0921\u093c\u0947 \u0921\u0947\u091f\u093e\u0938\u0947\u091f \u0938\u0947 \u0928\u093f\u092a\u091f \u0938\u0915\u0924\u093e \u0939\u0948\u0964<\/li>\n<li><strong>FLEXIBILITY<\/strong>\u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0925\u094d\u092e, \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0914\u0930 \u0906\u0930\u0902\u092d\u0940\u0915\u0930\u0923 \u092c\u093f\u0902\u0926\u0941 \u0915\u0947 \u0906\u0927\u093e\u0930 \u092a\u0930, \u0938\u094d\u0925\u093e\u0928\u0940\u092f \u092f\u093e \u0935\u0948\u0936\u094d\u0935\u093f\u0915 \u0928\u094d\u092f\u0942\u0928\u0924\u092e \u092e\u093e\u0928 \u091c\u094d\u091e\u093e\u0924 \u0915\u0930 \u0938\u0915\u0924\u093e \u0939\u0948\u0964<\/li>\n<\/ol>\n<h2>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0905\u0935\u0930\u094b\u0939\u0923 \u0915\u0947 \u092a\u094d\u0930\u0915\u093e\u0930<\/h2>\n<p>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0926\u092e \u0915\u0947 \u0924\u0940\u0928 \u092e\u0941\u0916\u094d\u092f \u092a\u094d\u0930\u0915\u093e\u0930 \u0939\u0948\u0902, \u091c\u093f\u0928\u094d\u0939\u0947\u0902 \u0921\u0947\u091f\u093e \u0915\u0947 \u0909\u092a\u092f\u094b\u0917 \u0915\u0947 \u0906\u0927\u093e\u0930 \u092a\u0930 \u0935\u093f\u092d\u0947\u0926\u093f\u0924 \u0915\u093f\u092f\u093e \u091c\u093e\u0924\u093e \u0939\u0948:<\/p>\n<ol>\n<li><strong>\u092c\u0948\u091a \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0905\u0935\u0930\u094b\u0939\u0923<\/strong>\u092e\u0942\u0932 \u0930\u0942\u092a, \u091c\u094b \u092a\u094d\u0930\u0924\u094d\u092f\u0947\u0915 \u091a\u0930\u0923 \u092a\u0930 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0915\u0940 \u0917\u0923\u0928\u093e \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0938\u0902\u092a\u0942\u0930\u094d\u0923 \u0921\u0947\u091f\u093e\u0938\u0947\u091f \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0924\u093e \u0939\u0948\u0964<\/li>\n<li><strong>\u0938\u094d\u091f\u094b\u091a\u0948\u0938\u094d\u091f\u093f\u0915 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f (\u090f\u0938\u091c\u0940\u0921\u0940)<\/strong>\u092a\u094d\u0930\u0924\u094d\u092f\u0947\u0915 \u091a\u0930\u0923 \u0915\u0947 \u0932\u093f\u090f \u0938\u092e\u0938\u094d\u0924 \u0921\u0947\u091f\u093e \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0928\u0947 \u0915\u0947 \u092c\u091c\u093e\u092f, SGD \u090f\u0915 \u092f\u093e\u0926\u0943\u091a\u094d\u091b\u093f\u0915 \u0921\u0947\u091f\u093e \u092c\u093f\u0902\u0926\u0941 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0924\u093e \u0939\u0948\u0964<\/li>\n<li><strong>\u092e\u093f\u0928\u0940-\u092c\u0948\u091a \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0905\u0935\u0930\u094b\u0939\u0923<\/strong>\u092c\u0948\u091a \u0914\u0930 \u090f\u0938\u091c\u0940\u0921\u0940 \u0915\u0947 \u092c\u0940\u091a \u090f\u0915 \u0938\u092e\u091d\u094c\u0924\u093e, \u092e\u093f\u0928\u0940-\u092c\u0948\u091a \u092a\u094d\u0930\u0924\u094d\u092f\u0947\u0915 \u091a\u0930\u0923 \u0915\u0947 \u0932\u093f\u090f \u0921\u0947\u091f\u093e \u0915\u0947 \u090f\u0915 \u0909\u092a\u0938\u092e\u0942\u0939 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0924\u093e \u0939\u0948\u0964<\/li>\n<\/ol>\n<h2>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0932\u093e\u0917\u0942 \u0915\u0930\u0928\u093e: \u092e\u0941\u0926\u094d\u0926\u0947 \u0914\u0930 \u0938\u092e\u093e\u0927\u093e\u0928<\/h2>\n<p>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u093e \u0907\u0938\u094d\u0924\u0947\u092e\u093e\u0932 \u0906\u092e\u0924\u094c\u0930 \u092a\u0930 \u092e\u0936\u0940\u0928 \u0932\u0930\u094d\u0928\u093f\u0902\u0917 \u092e\u0947\u0902 \u0932\u0940\u0928\u093f\u092f\u0930 \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928, \u0932\u0949\u091c\u093f\u0938\u094d\u091f\u093f\u0915 \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928 \u0914\u0930 \u0928\u094d\u092f\u0942\u0930\u0932 \u0928\u0947\u091f\u0935\u0930\u094d\u0915 \u091c\u0948\u0938\u0947 \u0915\u093e\u0930\u094d\u092f\u094b\u0902 \u0915\u0947 \u0932\u093f\u090f \u0915\u093f\u092f\u093e \u091c\u093e\u0924\u093e \u0939\u0948\u0964 \u0939\u093e\u0932\u093e\u0901\u0915\u093f, \u0915\u0908 \u0938\u092e\u0938\u094d\u092f\u093e\u090f\u0901 \u0909\u0924\u094d\u092a\u0928\u094d\u0928 \u0939\u094b \u0938\u0915\u0924\u0940 \u0939\u0948\u0902:<\/p>\n<ol>\n<li><strong>\u0938\u094d\u0925\u093e\u0928\u0940\u092f \u092e\u093f\u0928\u093f\u092e\u093e<\/strong>: \u091c\u092c \u0935\u0948\u0936\u094d\u0935\u093f\u0915 \u0928\u094d\u092f\u0942\u0928\u0924\u092e \u092e\u094c\u091c\u0942\u0926 \u0939\u094b \u0924\u094b \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0925\u094d\u092e \u0938\u094d\u0925\u093e\u0928\u0940\u092f \u0928\u094d\u092f\u0942\u0928\u0924\u092e \u092e\u0947\u0902 \u092b\u0902\u0938 \u0938\u0915\u0924\u093e \u0939\u0948\u0964 \u0938\u092e\u093e\u0927\u093e\u0928: \u0915\u0908 \u0906\u0930\u0902\u092d\u0940\u0915\u0930\u0923 \u0907\u0938 \u0938\u092e\u0938\u094d\u092f\u093e \u0915\u094b \u0926\u0942\u0930 \u0915\u0930\u0928\u0947 \u092e\u0947\u0902 \u092e\u0926\u0926 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964<\/li>\n<li><strong>\u0927\u0940\u092e\u0940 \u0905\u092d\u093f\u0938\u0930\u0923<\/strong>: \u092f\u0926\u093f \u0938\u0940\u0916\u0928\u0947 \u0915\u0940 \u0926\u0930 \u092c\u0939\u0941\u0924 \u0915\u092e \u0939\u0948, \u0924\u094b \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0925\u094d\u092e \u092c\u0939\u0941\u0924 \u0927\u0940\u092e\u093e \u0939\u094b \u0938\u0915\u0924\u093e \u0939\u0948\u0964 \u0938\u092e\u093e\u0927\u093e\u0928: \u0905\u0928\u0941\u0915\u0942\u0932\u0940 \u0938\u0940\u0916\u0928\u0947 \u0915\u0940 \u0926\u0930\u0947\u0902 \u0905\u092d\u093f\u0938\u0930\u0923 \u0915\u094b \u0917\u0924\u093f \u0926\u0947\u0928\u0947 \u092e\u0947\u0902 \u092e\u0926\u0926 \u0915\u0930 \u0938\u0915\u0924\u0940 \u0939\u0948\u0902\u0964<\/li>\n<li><strong>\u0913\u0935\u0930\u0936\u0942\u091f\u093f\u0902\u0917<\/strong>: \u092f\u0926\u093f \u0938\u0940\u0916\u0928\u0947 \u0915\u0940 \u0926\u0930 \u092c\u0939\u0941\u0924 \u092c\u0921\u093c\u0940 \u0939\u0948, \u0924\u094b \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0925\u094d\u092e \u0928\u094d\u092f\u0942\u0928\u0924\u092e \u0938\u0947 \u091a\u0942\u0915 \u0938\u0915\u0924\u093e \u0939\u0948\u0964 \u0938\u092e\u093e\u0927\u093e\u0928: \u092b\u093f\u0930 \u0938\u0947, \u0905\u0928\u0941\u0915\u0942\u0932\u0940 \u0938\u0940\u0916\u0928\u0947 \u0915\u0940 \u0926\u0930 \u090f\u0915 \u0905\u091a\u094d\u091b\u093e \u092a\u094d\u0930\u0924\u093f\u0935\u093e\u0926 \u0939\u0948\u0964<\/li>\n<\/ol>\n<h2>\u0938\u092e\u093e\u0928 \u0905\u0928\u0941\u0915\u0942\u0932\u0928 \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0926\u092e \u0915\u0947 \u0938\u093e\u0925 \u0924\u0941\u0932\u0928\u093e<\/h2>\n<table>\n<thead>\n<tr>\n<th>\u0915\u0932\u0928 \u0935\u093f\u0927\u093f<\/th>\n<th>\u0930\u092b\u093c\u094d\u0924\u093e\u0930<\/th>\n<th>\u0938\u094d\u0925\u093e\u0928\u0940\u092f \u0928\u094d\u092f\u0942\u0928\u0924\u092e \u091c\u094b\u0916\u093f\u092e<\/th>\n<th>\u0915\u0902\u092a\u094d\u092f\u0942\u091f\u0930 \u0938\u0902\u092c\u0902\u0927\u0940 \u0924\u0940\u0935\u094d\u0930\u0924\u093e<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u0922\u0924\u0932\u093e \u0939\u0941\u0906 \u0935\u0902\u0936<\/td>\n<td>\u092e\u0927\u094d\u092f\u092e<\/td>\n<td>\u0909\u091a\u094d\u091a<\/td>\n<td>\u0939\u093e\u0901<\/td>\n<\/tr>\n<tr>\n<td>\u0938\u094d\u091f\u094b\u091a\u0948\u0938\u094d\u091f\u093f\u0915 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f<\/td>\n<td>\u0924\u0947\u091c\u093c<\/td>\n<td>\u0915\u092e<\/td>\n<td>\u0928\u0939\u0940\u0902<\/td>\n<\/tr>\n<tr>\n<td>\u0928\u094d\u092f\u0942\u091f\u0928 \u0915\u0940 \u0935\u093f\u0927\u093f<\/td>\n<td>\u0927\u0940\u092e\u093e<\/td>\n<td>\u0915\u092e<\/td>\n<td>\u0939\u093e\u0901<\/td>\n<\/tr>\n<tr>\n<td>\u0906\u0928\u0941\u0935\u0902\u0936\u093f\u0915 \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0926\u092e<\/td>\n<td>\u091a\u0930<\/td>\n<td>\u0915\u092e<\/td>\n<td>\u0939\u093e\u0901<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u092d\u0935\u093f\u0937\u094d\u092f \u0915\u0940 \u0938\u0902\u092d\u093e\u0935\u0928\u093e\u090f\u0902 \u0914\u0930 \u0924\u0915\u0928\u0940\u0915\u0940 \u0935\u093f\u0915\u093e\u0938<\/h2>\n<p>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0926\u092e \u0915\u093e \u0907\u0938\u094d\u0924\u0947\u092e\u093e\u0932 \u092a\u0939\u0932\u0947 \u0938\u0947 \u0939\u0940 \u092e\u0936\u0940\u0928 \u0932\u0930\u094d\u0928\u093f\u0902\u0917 \u092e\u0947\u0902 \u0935\u094d\u092f\u093e\u092a\u0915 \u0930\u0942\u092a \u0938\u0947 \u0915\u093f\u092f\u093e \u091c\u093e \u0930\u0939\u093e \u0939\u0948, \u0932\u0947\u0915\u093f\u0928 \u091a\u0932 \u0930\u0939\u0947 \u0936\u094b\u0927 \u0914\u0930 \u0924\u0915\u0928\u0940\u0915\u0940 \u092a\u094d\u0930\u0917\u0924\u093f \u0938\u0947 \u0907\u0938\u0915\u0947 \u0914\u0930 \u092d\u0940 \u0905\u0927\u093f\u0915 \u0909\u092a\u092f\u094b\u0917 \u0915\u093e \u0935\u093e\u0926\u093e \u0915\u093f\u092f\u093e \u091c\u093e \u0930\u0939\u093e \u0939\u0948\u0964 \u0915\u094d\u0935\u093e\u0902\u091f\u092e \u0915\u0902\u092a\u094d\u092f\u0942\u091f\u093f\u0902\u0917 \u0915\u0947 \u0935\u093f\u0915\u093e\u0938 \u0938\u0947 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0926\u092e \u0915\u0940 \u0926\u0915\u094d\u0937\u0924\u093e \u092e\u0947\u0902 \u0938\u0902\u092d\u093e\u0935\u093f\u0924 \u0930\u0942\u092a \u0938\u0947 \u0915\u094d\u0930\u093e\u0902\u0924\u093f \u0906 \u0938\u0915\u0924\u0940 \u0939\u0948, \u0914\u0930 \u0926\u0915\u094d\u0937\u0924\u093e \u092e\u0947\u0902 \u0938\u0941\u0927\u093e\u0930 \u0915\u0930\u0928\u0947 \u0914\u0930 \u0938\u094d\u0925\u093e\u0928\u0940\u092f \u0928\u094d\u092f\u0942\u0928\u0924\u092e \u0938\u0947 \u092c\u091a\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0909\u0928\u094d\u0928\u0924 \u0935\u0947\u0930\u093f\u090f\u0902\u091f \u0932\u0917\u093e\u0924\u093e\u0930 \u0935\u093f\u0915\u0938\u093f\u0924 \u0915\u093f\u090f \u091c\u093e \u0930\u0939\u0947 \u0939\u0948\u0902\u0964<\/p>\n<h2>\u092a\u094d\u0930\u0949\u0915\u094d\u0938\u0940 \u0938\u0930\u094d\u0935\u0930 \u0914\u0930 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u093e \u0905\u0902\u0924\u0930\u094d\u0938\u0902\u092c\u0902\u0927<\/h2>\n<p>\u091c\u092c\u0915\u093f \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0906\u092e \u0924\u094c\u0930 \u092a\u0930 \u0921\u0947\u091f\u093e \u0935\u093f\u091c\u094d\u091e\u093e\u0928 \u0914\u0930 \u092e\u0936\u0940\u0928 \u0932\u0930\u094d\u0928\u093f\u0902\u0917 \u092e\u0947\u0902 \u0915\u093f\u092f\u093e \u091c\u093e\u0924\u093e \u0939\u0948, \u092f\u0939 \u092a\u094d\u0930\u0949\u0915\u094d\u0938\u0940 \u0938\u0930\u094d\u0935\u0930 \u0915\u0947 \u0938\u0902\u091a\u093e\u0932\u0928 \u092a\u0930 \u0938\u0940\u0927\u0947 \u0932\u093e\u0917\u0942 \u0928\u0939\u0940\u0902 \u0939\u094b\u0924\u093e \u0939\u0948\u0964 \u0939\u093e\u0932\u093e\u0901\u0915\u093f, \u092a\u094d\u0930\u0949\u0915\u094d\u0938\u0940 \u0938\u0930\u094d\u0935\u0930 \u0905\u0915\u094d\u0938\u0930 \u092e\u0936\u0940\u0928 \u0932\u0930\u094d\u0928\u093f\u0902\u0917 \u0915\u0947 \u0932\u093f\u090f \u0921\u0947\u091f\u093e \u0938\u0902\u0917\u094d\u0930\u0939 \u0915\u093e \u090f\u0915 \u0939\u093f\u0938\u094d\u0938\u093e \u092c\u0928\u0924\u0947 \u0939\u0948\u0902, \u091c\u0939\u093e\u0901 \u0921\u0947\u091f\u093e \u0935\u0948\u091c\u094d\u091e\u093e\u0928\u093f\u0915 \u0909\u092a\u092f\u094b\u0917\u0915\u0930\u094d\u0924\u093e \u0915\u0940 \u0917\u0941\u092e\u0928\u093e\u092e\u0940 \u092c\u0928\u093e\u090f \u0930\u0916\u0924\u0947 \u0939\u0941\u090f \u0935\u093f\u092d\u093f\u0928\u094d\u0928 \u0938\u094d\u0930\u094b\u0924\u094b\u0902 \u0938\u0947 \u0921\u0947\u091f\u093e \u090f\u0915\u0924\u094d\u0930 \u0915\u0930\u0924\u0947 \u0939\u0948\u0902\u0964 \u0907\u0928 \u092a\u0930\u093f\u0926\u0943\u0936\u094d\u092f\u094b\u0902 \u092e\u0947\u0902, \u090f\u0915\u0924\u094d\u0930\u093f\u0924 \u0921\u0947\u091f\u093e \u0915\u094b \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u090f\u0932\u094d\u0917\u094b\u0930\u093f\u0926\u092e \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930\u0915\u0947 \u0905\u0928\u0941\u0915\u0942\u0932\u093f\u0924 \u0915\u093f\u092f\u093e \u091c\u093e \u0938\u0915\u0924\u093e \u0939\u0948\u0964<\/p>\n<h2>\u0938\u092e\u094d\u092c\u0902\u0927\u093f\u0924 \u0932\u093f\u0902\u0915\u094d\u0938<\/h2>\n<p>\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u092a\u0930 \u0905\u0927\u093f\u0915 \u091c\u093e\u0928\u0915\u093e\u0930\u0940 \u0915\u0947 \u0932\u093f\u090f \u0906\u092a \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0938\u0902\u0938\u093e\u0927\u0928\u094b\u0902 \u092a\u0930 \u091c\u093e \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/p>\n<ol>\n<li><a href=\"https:\/\/towardsdatascience.com\/gradient-descent-from-scratch-e8b75fa986cc\" target=\"_new\" rel=\"noopener nofollow\">\u0938\u094d\u0915\u094d\u0930\u0948\u091a \u0938\u0947 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0905\u0935\u0930\u094b\u0939\u0923<\/a> - \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u094b \u0932\u093e\u0917\u0942 \u0915\u0930\u0928\u0947 \u092a\u0930 \u090f\u0915 \u0935\u094d\u092f\u093e\u092a\u0915 \u092e\u093e\u0930\u094d\u0917\u0926\u0930\u094d\u0936\u093f\u0915\u093e\u0964<\/li>\n<li><a href=\"https:\/\/www.kdnuggets.com\/2020\/02\/understanding-gradient-descent-mathematics.html\" target=\"_new\" rel=\"noopener nofollow\">\u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u0947 \u0917\u0923\u093f\u0924 \u0915\u094b \u0938\u092e\u091d\u0928\u093e<\/a> - \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u093e \u0935\u093f\u0938\u094d\u0924\u0943\u0924 \u0917\u0923\u093f\u0924\u0940\u092f \u0905\u0928\u094d\u0935\u0947\u0937\u0923\u0964<\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.linear_model.SGDRegressor.html\" target=\"_new\" rel=\"noopener nofollow\">Scikit-Learn \u0915\u093e SGDRegressor<\/a> - \u092a\u093e\u092f\u0925\u0928 \u0915\u0940 \u0938\u094d\u0915\u093f\u0915\u093f\u091f-\u0932\u0930\u094d\u0928 \u0932\u093e\u0907\u092c\u094d\u0930\u0947\u0930\u0940 \u092e\u0947\u0902 \u0938\u094d\u091f\u094b\u091a\u0948\u0938\u094d\u091f\u093f\u0915 \u0917\u094d\u0930\u0947\u0921\u093f\u090f\u0902\u091f \u0921\u093f\u0938\u0947\u0902\u091f \u0915\u093e \u090f\u0915 \u0935\u094d\u092f\u093e\u0935\u0939\u093e\u0930\u093f\u0915 \u0905\u0928\u0941\u092a\u094d\u0930\u092f\u094b\u0917\u0964<\/li>\n<\/ol>","protected":false},"featured_media":468485,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477370","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Gradient Descent: The Core of Optimizing Complex Functions<\/mark>","faq_items":[{"question":"What is Gradient Descent?","answer":"<p>Gradient Descent is an optimization algorithm used to find the minimum of a function. It is often used in machine learning and data science to optimize complex functions that are difficult or impossible to solve analytically.<\/p>"},{"question":"When was Gradient Descent first mentioned?","answer":"<p>The concept of gradient descent, rooted in calculus, was first described formally in a publication by the American Institute of Mathematical Sciences in 1847.<\/p>"},{"question":"How does Gradient Descent work?","answer":"<p>Gradient Descent works by taking iterative steps in the direction of the steepest descent of a function. It starts with an initial guess for the minimum of the function, computes the gradient of the function at that point, and then takes a step in the direction where the gradient is descending most rapidly.<\/p>"},{"question":"What are the key features of Gradient Descent?","answer":"<p>The key features of Gradient Descent include its robustness (it can handle functions with many variables), scalability (it can deal with large datasets using a variant called Stochastic Gradient Descent), and flexibility (it can find either local or global minima, depending on the function and initialization point).<\/p>"},{"question":"What types of Gradient Descent exist?","answer":"<p>Three main types of gradient descent algorithms exist: Batch Gradient Descent, which uses the entire dataset to compute the gradient at each step; Stochastic Gradient Descent (SGD), which uses one random data point at each step; and Mini-Batch Gradient Descent, which uses a subset of the data at each step.<\/p>"},{"question":"Where is Gradient Descent used and what problems can arise?","answer":"<p>Gradient Descent is commonly used in machine learning for tasks like linear regression, logistic regression, and neural networks. However, issues can arise, such as getting stuck in local minima, slow convergence if the learning rate is too small, or overshooting the minimum if the learning rate is too large.<\/p>"},{"question":"How does Gradient Descent compare to other optimization algorithms?","answer":"<p>Gradient Descent is generally more robust than other methods like Newton's Method and Genetic Algorithms but can risk getting stuck in local minima and can be computationally intensive. Stochastic Gradient Descent mitigates some of these issues by being faster and less likely to get stuck in local minima.<\/p>"},{"question":"What are the future prospects for Gradient Descent?","answer":"<p>Ongoing research and technological advancements, including the development of quantum computing, promise even greater utilization of gradient descent. Advanced variants are continually being developed to improve efficiency and avoid local minima.<\/p>"},{"question":"How can Gradient Descent be associated with proxy servers?","answer":"<p>While Gradient Descent is not directly applicable to the operations of proxy servers, proxy servers often form part of data collection for machine learning. In these scenarios, the collected data might be optimized using gradient descent algorithms.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/in\/wp-json\/wp\/v2\/wiki\/477370","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/in\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/in\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/in\/wp-json\/wp\/v2\/wiki\/477370\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/in\/wp-json\/wp\/v2\/media\/468485"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/in\/wp-json\/wp\/v2\/media?parent=477370"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}