Everything about Pooling layers and different types of Pooling
We have explored the idea and computation details behind pooling layers in Machine Learning models and different types of pooling operations as well. In short, the different types of pooling operations are Maximum Pool, Minimum Pool, Average Pool and Adaptive Pool.
Purpose of different layers in a Deep Learning Model
In this article, we have explored the significance or the importance of each layer in a Machine Learning model. Different layers include convolution, pooling, normalization and much more. For example: the significance of MaxPool is that it decreases sensitivity to the location of features.