In this blog, we will be understanding the concept of weight pruning with Keras. Basically, weight pruning is a model optimization technique. In weight pruning, it gradually zeroes out model weight during the training process to achieve model sparsity.

This technique brings improvements via model compression. This technique is widely used to decrease the latency of the model.

I will be implementing weight pruning in the Fashion MNIST dataset where I have made a comparison between the normal way and the pruning method.

#machine-learning #deep-learning #keras #tensorflow #tflite