Gradient Descent, Data Science, Data Visualization, Deep Learning, Machine Learning.
self.coef_ = self.coef_ - (self.lr * coef_der) print(self.intercept_,self.coef_) def predict(self,X_test): return np.dot(X_test,self.coef_) + self.intercept_ sgd = SGDRegressor(learning_rate=0.01,epochs=40) start = time.time() sgd.fit(X_train,y_train) print("The time taken is",time.time() - start)