A collection of helpful resources for working with Deep Learning and Keras

## Keras (with Tensoflow)

- How to generate data on the fly with Keras
- Callbacks - Keras Documentation
- Monitor progress of your Keras based neural network using Tensorboard
- Keras Tutorial : Fine-tuning pre-trained models - Learn OpenCV
- Keras gist for adding checkpoints to Models

## Troubleshooting

- 37 Reasons why your Neural Network is not working – Slav
- 3.2. Tuning the hyper-parameters of an estimator — scikit-learn 0.20.2 documentation
- Troubleshooting Convolutional Neural Nets
- A Recipe for Training Neural Networks

## Deep Learning Theory

- jgvictores/awesome-deep-reinforcement-learning: Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines…
- CS231n Convolutional Neural Networks for Visual Recognition
- 5 Regression Loss Functions All Machine Learners Should Know
- Differences between the L1-norm and the L2-norm (Least Absolute Deviations and Least Squares)