How can I optimize my machine learning model training?

How can I optimize my machine learning model training?

To optimize your model training, consider techniques like hyperparameter tuning, using better algorithms, and data augmentation.

What is hyperparameter tuning and how do I do it?

Hyperparameter tuning involves adjusting the parameters that govern the training process. You can use methods like grid search or random search.

Are there specific libraries that can help with this?

Yes, libraries like Scikit-learn, Optuna, and Hyperopt are great for hyperparameter tuning.

How does data augmentation improve model performance?

Data augmentation increases the diversity of your training dataset by creating modified versions of existing data, which helps prevent overfitting.