Notes on All Things Machine Learning and Mathematics

Deep Learning: The book

Introduction

Linear algebra

Probability and information theory

Machine learning basics

Numerical computation

Optimization for training deep models

Deep feed forward networks

Regularization for deep learning

Practical methodology

Convolutional networks

Sequence modeling & RNNs

Application tips

Generative adversarial networks

Variantional Autoencoders