Glossary term
Glossary term
Training and Fine-Tuning
Hyperparameter tuning optimizes settings that control how an AI model learns, like learning rate or model size, improving accuracy, speed, and reliability without changing the model's core architecture.
Optuna and Ray Tune are widely used open-source libraries for hyperparameter tuning in ML pipelines.
Weights & Biases Sweeps and SageMaker Automatic Model Tuning provide managed hyperparameter optimisation.
Google Vertex AI Vizier and Azure ML HyperDrive automate hyperparameter search at scale.