Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks

Table of Contents

1. Linear Algebra
2. Vector Calculus
3. Probability and Statistics
4. Optimization
5. Graph Theory
6. Linear Neural Networks
7. Feedforward Neural Networks
8. Regularization
9. Convolutional Neural Networks
10. Recurrent Neural Networks
11. Attention Mechanisms
12. Generative Models
13. Transfer and Meta Learning
14. Geometric Deep Learning