What are the best practices for using Keras in deep learning?

What are the best practices for using Keras in deep learning?

Some best practices include using the Functional API for complex models, regularization techniques, and proper data preprocessing.

Can you explain why the Functional API is preferred for complex models?

The Functional API allows for more flexibility in building models, enabling the creation of multi-input and multi-output models.

What regularization techniques should I consider?

You should consider techniques like Dropout, L2 regularization, and Batch Normalization to prevent overfitting.

How important is data preprocessing?

Data preprocessing is crucial as it ensures that your model receives clean, normalized data, which can significantly improve performance.

Any tips for optimizing model performance?

Yes, you can try techniques like learning rate scheduling, early stopping, and using callbacks to monitor performance during training.