Tutorials for deep learning frameworks (PyTorch/JAX/Tensorflow) JAX: Clean, NumPy-like API Excellent support for forward derivatives and higher-order derivatives Functional style, user maintains state explicitly. Avoids lots of potential bugs (especially random number generation).