How can I optimize my deep learning model for better performance?

How can I optimize my deep learning model for better performance?

There are several strategies you can use, such as tuning hyperparameters, using regularization techniques, and optimizing your data preprocessing.

What hyperparameters should I focus on tuning?

Key hyperparameters include learning rate, batch size, number of epochs, and the architecture of the model itself.

Can you explain how regularization helps?

Regularization techniques like L1 and L2 help prevent overfitting by adding a penalty for larger weights, encouraging simpler models.

What data preprocessing steps are important?

Important steps include normalization, handling missing values, and data augmentation to improve model robustness.