Contents:
1. ai4water datasts
2. working with large data
3. multi-output neural network
4. multi-input neural network
5. using conditional RNN
6. Quantile regression
7. Autoencoders and variational autoencoders
8. using third party models
9. customizing training loop in tensorflow
10. customizing training loop in pytorch
11. customizing loss function in tensorflow
12. customizing loss function in pytorch
