What are the best practices for using TensorFlow and Keras?

What are the best practices for using TensorFlow and Keras?

Some best practices include using the Keras functional API for complex models, ensuring proper data preprocessing, and utilizing callbacks for better training management.

Can you explain why data preprocessing is important?

Data preprocessing is crucial as it helps improve model accuracy by ensuring that the data is clean, normalized, and in the right format for training.

What are some common callbacks I should use?

Common callbacks include EarlyStopping to prevent overfitting, ModelCheckpoint to save the best model, and ReduceLROnPlateau to adjust the learning rate.

How can I monitor my model's performance during training?

You can use TensorBoard for visualizing metrics like loss and accuracy during training, which helps in understanding model performance.