Gradient descent, how neural networks learn | Chapter 2, deep learning

Gradient descent, how neural networks learn | Chapter 2, deep learning

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Math topics:
_Functions_and_mappings_##Functions and mappings##_Graph_of_a_function_##Graph of a function##_Function_(mathematics)_##Function (mathematics)##_Row_and_column_vectors_##Row and column vectors##_Function_composition_##Function composition##_Mathematical_optimization_##Mathematical optimization##_Maxima_and_minima_##Maxima and minima##_Mathematical_optimization_##Mathematical optimization##_Gradient_descent_##Gradient descent##_Multivariable_calculus_##Multivariable calculus##_Gradient_##Gradient##_Multivariable_calculus_##Multivariable calculus##_Euclidean_vector_##Euclidean vector##_Mathematical_modeling_##Mathematical modeling##_Deep_learning_##Deep learning##_Artificial_neural_network_##Artificial neural network##_Lambda_calculus_##Lambda calculus##_Geometry_##Geometry##_Point_(geometry)_##Point (geometry)##_Space_##Space##_Continuous_function_##Continuous function##_Cartesian_coordinate_system_##Cartesian coordinate system
Other topics:
_Machine_learning_##Machine learning##_Statistical_classification_##Statistical classification##_Machine_learning_##Machine learning##_Loss_function_##Loss function##_Physics_##Physics##_Causality_##Causality##_Dimension_##Dimension##_Linearity_##Linearity##_Syntax_(logic)_##Syntax (logic)##_Logical_consequence_##Logical consequence##_Variable_(mathematics)_##Variable (mathematics)##_Rule_of_inference_##Rule of inference
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