Introduction 3 Topics

Introduction to neural networks 12 Topics

Setting up the environment 8 Topics

Minimal Example – your first machine learning algorithm 4 Topics

TensorFlow – An Introduction 7 Topics

Going deeper : Introduction to deep neural networks 8 Topics

Overfitting 6 Topics

Initialization 3 Topics

Gradient descent and learning rates 7 Topics

Preprocessing 5 Topics

The MNIST example 9 Topics

Business Case 8 Topics

Appendix: Linear Algebra Fundamentals 11 Topics