Deep Learning CNN Convolutional Neural Networks with Python - Batch Normalization

The video tutorial discusses the concept of mini batches in gradient descent, highlighting the assumption that all mini batches have the same distribution. It introduces the issue of covariate shift, where this assumption is violated, and presents batch normalization as a solution. Batch normalization standardizes features to have a mean of zero and a standard deviation of one, which helps in resolving covariate shift and provides regularization benefits. The process is applied layer-wise in neural networks, improving convergence speed and addressing gradient problems. The video concludes with a mention of upcoming topics on learning rates.

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