Grokking Deep Learning

3.1. What am I going to learn in this chapter? 3.2. What is a Neural Network? 3.3. What does a Neural Network do? 3.4. Does the network make accurate predictions? 3.5. Why measure error? 3.6. What the Simplest Form of Neural Network Learning? 3.7. Characteristics of Hot and Cold Learning 3.8. Calculating Both direction and amount from error 3.9. Learning Is Just Reducing Error 3.10. Let’s Back Up And Talk about Functions 3.11. Tunnel Vision on One Concept 3.12. Relationship Exploration: Hot and Cold 3.13. A Box With Rods Poking Out of It 3.14. Derivatives…​ take Two 3.15. What you really need to know…​ 3.16. What you don’t really need to know…​ 3.17. How to use a derivative to learn 3.18. Where is our derivative in the code? 3.19. Learning…

Link to Full Article: Grokking Deep Learning

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