How can I optimize deep learning training processes?

How can I optimize deep learning training processes?

To optimize deep learning training, consider techniques like data augmentation, learning rate scheduling, and using pre-trained models.

What is data augmentation and how does it help?

Data augmentation involves creating modified versions of your training data to improve model generalization and reduce overfitting.

Can you explain learning rate scheduling?

Learning rate scheduling adjusts the learning rate during training, helping the model converge faster and avoid local minima.

What are some common pre-trained models I can use?

Common pre-trained models include VGG, ResNet, and BERT, which can be fine-tuned for specific tasks.