Tune

In this module, you’ll learn how to use Ray Tune to run distributed hyperparameter tuning, starting from a baseline PyTorch MNIST training loop and scaling experiments across available GPUs. By the end, you’ll be able to define a Tune training function, specify a search space, and execute parallel trials to find better-performing model configurations.