# Neural-network foundations

Subject: Deep Learning

Exam: MT2

Reader: https://deep-learning-study-room.vercel.app/#mt2/read/4

Canonical: https://deep-learning-study-room.vercel.app/read/dl/mt2/chapter/4/

Technical definitions, neuron models, activations, losses, forward propagation and backpropagation. These foundations support the MT2 calculations.

1. [What does learning from data mean](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s0/)
2. [Classification regression and learning types](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s2/)
3. [Training validation and test data](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s3/)
4. [Parameters and hyperparameters](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s4/)
5. [What one artificial neuron does](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s5/)
6. [Activation functions and how to calculate them](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s7/)
7. [Drill 8 Activation contrast](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s8/)
8. [Choosing a loss](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s9/)
9. [Drill 2 Half sum versus mean](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s2/)
10. [Drill 7 Sigmoid with binary cross entropy](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s7/)
11. [Drill 9 Softmax and true class loss](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s9/)
12. [Cross-entropy for probability distributions](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s17/)
13. [Forward propagation through multiple neurons](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s10/)
14. [Your first complete training step](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s1/)
15. [Complete sigmoid training example](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s16/)
16. [Drill 10 Sigmoid neuron gradient](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s10/)
17. [Backpropagation with one hidden neuron](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s11/)
18. [More outputs and vectorized backpropagation](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s12/)
19. [Drill 11 Full ReLU backpropagation](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s11/)
20. [Drill 12 Two output sigmoid backpropagation](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s12/)
21. [Drill 13 A negative ReLU blocks this path](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c17-s13/)
22. [Counting parameters in a dense network](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s14/)
23. [Teacher vectorized ReLU example](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s5/)
24. [Teams photos full sigmoid example](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s6/)
25. [MT1A Q2](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s0/)
26. [MT1A Q3](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s1/)
27. [MT1A Q4](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s2/)
28. [MT1B Q3](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s3/)
29. [MT1B Q4](https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c10-s4/)