Accelerate Model Training With Batch Normalization

The Batch Normalization paper published back in 2015 by Sergey Ioffe, Christian Szegedy took the deep learning community by storm. It became one of the most implemented techniques in deep learning after it was released. Notably, its ability to accelerate training of deep learning models and achieve the same accuracy in 14 times fewer training steps was a great catch. Indeed that brought in the attention which it gets today (who doesn't want to train faster?). And there's been a lot of similar papers like layer normalization, instance normalization and a few others.