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Chapter 9 - Backpropagation
Chapter 8: Gradients, Partial Derivatives,and the Chain Rule
Chapter 7 : Summary
Chapter 7: Analytical Derivative
Chapter 7:Derivatives
Chapter 6: Introducing Optimization
Chapter 5 :The Categorical Cross-Entropy Loss Class
Chapter 5: Calculating Network Error with Loss
Chapter 4:The Softmax Activation Function
Chapter 4:ReLU Activation Function Code
Chapter 4:Activation Functions
Chapter 3 Adding Layers: Dense Layer Class
Chapter 2: Coding Our First Neurons (A Batch of Data to A Layer of Neurons & Batch of Data w/ NumPy)
L1
Chapter 1:Introducing Neural Networks
Chapter 3:Adding Layers and Training Data
