Lecture - 28 Back Propagation Learning

Lecture - 28 Back Propagation Learning

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nptelhrd • 109K views

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Math topics:
_Elementary_mathematics_##Elementary mathematics##_Function_(mathematics)_##Function (mathematics)##_Argument_of_a_function_##Argument of a function##_Constant_(mathematics)_##Constant (mathematics)##_Elementary_arithmetic_##Elementary arithmetic##_Fraction_(mathematics)_##Fraction (mathematics)##_Subtraction_##Subtraction##_Plus_and_minus_signs_##Plus and minus signs##_Types_of_functions_##Types of functions##_Weight_function_##Weight function##_Continuous_function_##Continuous function##_Sigmoid_function_##Sigmoid function
Other topics:
_Artificial_neural_networks_##Artificial neural networks##_Activation_function_##Activation function##_Artificial_neural_network_##Artificial neural network##_Artificial_neuron_##Artificial neuron##_Backpropagation_##Backpropagation##_Perceptron_##Perceptron##_Physics_##Physics##_Vector_space_##Vector space##_Euclidean_vector_##Euclidean vector##_Dimension_##Dimension##_Statistical_deviation_and_dispersion_##Statistical deviation and dispersion##_Root-mean-square_deviation_##Root-mean-square deviation##_Errors_and_residuals_##Errors and residuals##_Root_mean_square_##Root mean square##_Metaphysics_##Metaphysics##_Information_##Information##_Subroutine_##Subroutine##_Information_theory_##Information theory##_Analysis_##Analysis##_Derivative_##Derivative##_Partial_function_##Partial function##_Decision_tree_##Decision tree
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