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In this guide we discuss the most common advanced uses cases of PyHopper.

• NumPy parameters
• Search history
• Checkpointing
• Pruners
• NaNs and Exceptions
• Tensorboard integration
• MLflow and Weights & Biases callback
• Cross-validation
• Custom sampling strategies
• Custom parameter types
• Custom Callbacks