Need of Batch Normalization || Lesson 18 || Deep Learning || Learning Monkey || скачать в хорошем качестве

Need of Batch Normalization || Lesson 18 || Deep Learning || Learning Monkey ||

#deeplearning#learningmonkey#neuralnetwork In this class, we discuss the need for batch normalization. In our neural network, we use batch gradient descent. We send the data into our network in batches. As the distribution of batch changes a little. The data moved in layers and multiplied with different values. The deep layers see a lot of change in data in each batch. This we call it internal covariance shift. Because of this covariance shift training, the data takes time. To normalize the data at each layer so that it will see each time from the same distribution. Weights are updated fast. That's the use of batch normalization. Link for playlists:    / @wisdomerscse   Link for our website: https://learningmonkey.in Follow us on Facebook @   / learningmonkey   Follow us on Instagram @   / learningmonkey1   Follow us on Twitter @   / _learningmonkey   Mail us @ learningmonkey01@gmail.com