Network pruning

Technique used in machine learning to reduce the size and complexity of neural networks by removing less important weights, neurons, or structures. This process helps in making models more efficient, leading to faster inference times and lower memory usage without significantly compromising performance. Network pruning is particularly beneficial for developers and researchers looking to deploy machine learning models on resource-constrained devices or environments.

Network pruning was discovered on March 30th 2022 and it currently has a search volume of 140 with a growth of -15%.