Normalize and Standardize Inputs
Scale features so training converges.
Raw Numbers Slow Learning
Features on wildly different scales, like age and salary, confuse a network. Rescaling them first is why normalization makes training converge faster. ⚖️
Two Common Recipes
You will meet two main scalers: standardization shifts data to mean zero and unit variance, while min-max squeezes it into a fixed range like 0 to 1.
All lessons in this course
- Write a Custom Dataset Class
- Batching, Shuffling & num_workers
- collate_fn for Variable-Length Inputs
- Normalize and Standardize Inputs