Setup AutoML Pipeline

See Extended Examples for complete configuration files and templates.

Automate hyperparameter tuning and model selection using Optuna or Ray Tune with efficient search strategies.

When to Use

• Starting new ML project and need to quickly find good model configurations
• Retraining existing model with new data and want to re-optimize hyperparameters
• Comparing multiple algorithms and their optimal configurations
• Limited time for manual tuning but need near-optimal performance
• Team lacks deep expertise in specific algorithm hyperparameters
• Need reproducible and documented optimization process

Inputs