Uploaded November 2021 | Updated September 2026, 1 week ago

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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)

Watch all Google's Machine Learning Virtual Community Day sessions → https://goo.gle/mlcommunityday-all

Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow

#MLCommunityDay


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