Hyperparameter Tuning

➺ Search Strategies:

  • Grid search
  • Random search
  • Bayesian optimization
  • Population-based training 

    • ➺ Implementation Framework:

    Key Parameters
  • Learning rate
  • Batch size
  • Model architecture
  • Regularization strength
    • Search Space Design 
  • Log-uniform sampling
  • Categorical parameters
  • Conditional spaces
  • Multi-objective optimization 
    • Advanced Techniques
  • Early stopping criteria
  • Pruning unpromising trials
  • Parallel evaluation
  • Resource allocation

    • ➺ Automation Tools:

  • Ray Tune
  • Optuna
  • Weights & Biases
  • MLflow integration