Deep Learning Book Notes
Hi there, these are a collection of notes for the Deep Learning Book.
These are still under construction, but if you see an error or would like something added, please feel free to send us a PR!
Part I: Applied Math and Machine Learning Basics
Chapter 3: Probability and Information Theory
Chapter 4: Numerical Computation
Chapter 5: Machine Learning Basics
Part II: Modern Practical Deep Networks
Chapter 6: Deep Feedforward Networks
Chapter 7: Regularization for Deep Learning
Chapter 8: Optimization for Deep Learning