YAIL (Yet another AI Library) ⛵
The goal is to provide all beginners (like us) with the resources to build their first neural network from scratch.
I'd rather redirect you to some incredible resources that already exist than trying to re-explain everything. If you go through the links you should feel comfortable with the explanations into the code
- 3B1B neural networks series: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
- Michael Nielsen's book (best explanations found beginner): https://neuralnetworksanddeeplearning.com/
- Book by Ian Goodfellow and Yoshua Bengio and Aaron Courville: https://www.deeplearningbook.org/
If you are not familiar with multivariable calculus check some videos from one of these series:
- https://www.youtube.com/playlist?list=PLSQl0a2vh4HC5feHa6Rc5c0wbRTx56nF7
- https://www.youtube.com/playlist?list=PL4C4C8A7D06566F38
| Optimizer |
|---|
| stochastic gradient descent |
| Loss |
|---|
| mean squared error |
| cross entropy |
| Activation |
|---|
| sigmoid |
| leaky relu |
softmax todo |
| Layer |
|---|
| flatten |
| dense |
conv todo |
max pool todo |