What are the best practices for optimizers in machine learning?

What are the best practices for optimizers in machine learning?

Some best practices include choosing the right optimizer for your model, tuning hyperparameters, and monitoring training.

Can you explain why hyperparameter tuning is important?

Hyperparameter tuning is crucial because it helps improve model performance by finding the optimal settings for learning.

What optimizers do you recommend for deep learning?

For deep learning, Adam, RMSprop, and SGD with momentum are popular choices due to their efficiency and effectiveness.

How do I know if my optimizer is working well?

You can monitor the loss and accuracy metrics during training. If they improve consistently, your optimizer is likely working well.