JAX is a library similar to NumPy, redesigned by Google for GPUs and TPUs. A wave of new ML frameworks, based on JAX, are looking for a chance to become an alternative to PyTorch and TensorFlow. In this session, I try out three JAX frameworks (Objax, Flax, and Elegy), showing the steps to solve Kaggle’s flower classification challenge with each one.
Date & Time: 7 November 2020, Saturday 10:45-11:15
Speaker: Nick Doiron
Nick is a Software Engineer at the MGGG Redistricting Lab. Previously he worked with One Laptop per Child, McKinsey, Code for America, and the Museum of Modern Art (NYC).