Data Science with Python — Hard
Key points
- Batch normalization stabilizes training by normalizing activations
- It allows for higher learning rates and acts as a regularizer
- Learnable scale and shift parameters are included
- Zero mean and unit variance are maintained within each mini-batch
Ready to go further?
Related questions