Lecture 9.2 — Neural Networks Learning | Backpropagation Algorithm — [ Machine Learning | Andrew Ng] Lecture 9.2 — Neural Networks Learning | Backpropagation Algorithm — [ Machine Learning | Andrew Ng] begin-post-stats Data Science Tutorials - All in One • 10K views end-post-stats begin-duration 12:00 end-duration Math topics: _Mathematical_analysis_##Mathematical analysis##_Derivative_##Derivative##_Calculus_##Calculus##_Partial_derivative_##Partial derivative##_Regression_analysis_##Regression analysis##_Dependent_and_independent_variables_##Dependent and independent variables##_MATLAB_##MATLAB##_Errors_and_residuals_##Errors and residuals##_Set_theory_##Set theory##_First-order_logic_##First-order logic##_Function_(mathematics)_##Function (mathematics)##_Element_(mathematics)_##Element (mathematics)##_Philosophy_of_mathematics_##Philosophy of mathematics##_Algorithm_##Algorithm##_Transpose_##Transpose##_Mathematical_proof_##Mathematical proof Other topics: _Artificial_neural_networks_##Artificial neural networks##_Activation_function_##Activation function##_Artificial_neural_network_##Artificial neural network##_Backpropagation_##Backpropagation##_Physics_##Physics##_Euclidean_vector_##Euclidean vector##_Time_##Time##_W_and_Z_bosons_##W and Z bosons video-id: x_Eamf8MHwU channel_Data_Science_Tutorials_-_All_in_One_ So What Learning Artificial neural networks , Mathematical analysis , Philosophy of mathematics , Physics , Regression analysis , Set theory Saturday, January 20, 2018 Share Share