How can I optimize the performance of my machine learning model?
To optimize your model's performance, you can start by tuning hyperparameters, selecting the right features, and using cross-validation.
What are some common hyperparameters I should consider tuning?
Common hyperparameters include learning rate, batch size, number of epochs, and regularization parameters.
How does feature selection impact model performance?
Feature selection can significantly improve model performance by reducing overfitting and improving generalization.
Can you recommend any tools for hyperparameter tuning?
Yes, popular tools include GridSearchCV, RandomizedSearchCV, and libraries like Optuna and Hyperopt.
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