JAX is a Python package that combines a NumPy-like API with a set of powerful composable transformations for automatic differentiation, vectorization, parallelization, and JIT compilation. Your code can run on CPU, GPU or TPU. This talk will get you started accelerating your ML with JAX!

Resources:
JAX reference documentation → https://goo.gle/3BoqAIM

Speaker:
Jake VanderPlas (Software Engineer)

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product: TensorFlow - General; event: ML Community Day 2021; fullname: Jake VanderPlas; re_ty: Publish;