The Maths behind Neural Networks

Alex Punnen
© All Rights Reserved

Contents

• Chapter 1: The simplest Neural Network - Perceptron using Vectors and Dot Products
• Chapter 2: Perceptron Training via Feature Vectors & HyperPlane split
• Chapter 3: Gradient Descent and Optimization
• Chapter 4: Back Propagation - Pass 1 (Chain Rule)
• Chapter 5: Back propagation - Pass 2 (Scalar Calculus)
• Chapter 6: A Simple NeuralNet with Back Propagation
• Chapter 7: Back Propagation Pass 3 (Matrix Calculus)
• Chapter 8: Back Propagation in Full - With Softmax & CrossEntropy Loss