How can I optimize my machine learning model in Python?
You can optimize your model by tuning hyperparameters, using feature selection, and applying regularization techniques.
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 grid search in more detail?
Grid search is a method where you define a grid of hyperparameter values and evaluate the model's performance for each combination.
Are there any libraries in Python that can help with this?
Yes, libraries like Scikit-learn provide built-in functions for grid search and hyperparameter tuning.
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