Intro to JAX: Accelerating Machine Learning research
Автор: TensorFlow
Загружено: 2021-11-11
Просмотров: 1854633
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;
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