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Study mode:
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1
My get started with JAX repo
2
Stateful to stateless conversion
3
PyTrees in depth
4
Training an MLP in pure JAX
5
Custom PyTrees
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Parallelism in JAX TPUs example
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Communication between devices
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value_and_grad and has_aux
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Training an ML model on multiple machines
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stop grad, per example grads
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Implementing MAML in 3 lines
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Outro
Description:
Dive into advanced machine learning concepts with JAX in this comprehensive tutorial video. Learn to convert stateful models to stateless, master PyTrees, and train a multilayer perceptron using pure JAX. Explore custom PyTrees, parallelism with TPUs, and inter-device communication. Discover techniques for training models across multiple machines, implementing per-example gradients, and even tackle meta-learning with a 3-line MAML implementation. Gain practical insights into JAX's powerful features for building and optimizing complex machine learning models.

Machine Learning with JAX - From Hero to HeroPro+

Aleksa Gordić - The AI Epiphany
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