How to: Deep Learning
_Frameworks for Neural Networks and Deep Learning. Also see [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning)._

- [jax](https://github.com/google/jax) - a library for high-performance numerical computing with automatic differentiation and JIT compilation.
- [keras](https://github.com/keras-team/keras) - A high-level neural networks library and capable of running on top of either TensorFlow or Theano.
- [pytorch-lightning](https://github.com/Lightning-AI/pytorch-lightning) - Deep learning framework to train, deploy, and ship AI products Lightning fast.
- [pytorch](https://github.com/pytorch/pytorch) - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- [stable-baselines3](https://github.com/DLR-RM/stable-baselines3) - PyTorch implementations of Stable Baselines (deep) reinforcement learning algorithms.
- [tensorflow](https://github.com/tensorflow/tensorflow) - The most popular Deep Learning framework created by Google.