How to tune hyperparameters on XGBoost

This blog post is part 2 in a series on hyperparameter tuning, focusing on practical examples with XGBoost and the MNIST dataset. The authors provide step-by-step instructions on how to preprocess the data, build a model without hyperparameter tuning, tune hyperparameters using random search, and demonstrate improvements in accuracy. They also outline their plans for part 3, which will explore distributed hyperparameter tuning using Ray Tune.