Glossary · Phase 4 · Deep learning
Data augmentation
Making small random changes to training examples, such as shifting or flipping an image, so a model learns the pattern instead of memorizing pixels.
Try it now
A small batch gives many noisy steps per epoch. A large batch gives few smooth ones.
Learn it properly
Mini-batches and SGD · Train on small random batches instead of everything at once. About 30 minutes.
Other terms from the same lesson
- SGD: Gradient descent using a small random batch each step instead of all the data: noisier but much faster.
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