How can I optimize my machine learning models in Python?

How can I optimize my machine learning models in Python?

You can optimize your models by tuning hyperparameters, using cross-validation, and selecting the right algorithms.

What are hyperparameters, and how do I tune them?

Hyperparameters are settings that you configure before training your model. You can tune them using techniques like Grid Search or Random Search.

Can you explain cross-validation?

Cross-validation is a technique to assess how the results of a statistical analysis will generalize to an independent dataset. It helps in preventing overfitting.

What algorithms should I consider for optimization?

Consider algorithms like Random Forest, Gradient Boosting, or Support Vector Machines, as they often yield good results with proper tuning.