Hyperparameter Optimization Techniques in ML
Introduction to Hyperparameter Optimization
Hyperparameters control how a model learns. Unlike model parameters, they are set before training begins. Optimizing them can significantly improve performance.
Common Optimization Techniques
- Grid Search
- Random Search
- Bayesian Optimization
- Automated ML tuning systems
Production systems integrate tuning directly into training pipelines for continuous improvement.
