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JAX for ML Engineering

Build differentiable, accelerated numerical programs with JAX and measure their performance correctly.

All TracksAdvanced AI Interview LabJAX for ML EngineeringJevAgentic AI & Multi-Agent SystemsRAG UniversityLLM Engineering & Core TransformersDistributed Big Data EngineeringDistributed & AI System Design

JAX for ML Engineering

Build differentiable, accelerated numerical programs with JAX and measure their performance correctly.

Transformations & Training

From array operations to a compiled gradient step.

1 Lesson
Intermediate35 min

JAX: grad, jit and vmap in Practice

JAX combines NumPy-style arrays with program transformations for machine learning and scientific computing. Start with pure functions, then transform them into gradients, compiled programs or batches.