Optimizations are required to run training and inference of Neural Networks faster on a particular hardware infrastructure. It is important to maintain the accuracy of Neural Networks while applying various optimizations.
Read this article to understand the various types of neural network optimizations
Some of the Neural Network optimizations are:
- Weight pruning
- Structured pruning
- Knowledge distillation
- Conditional computation
This is a companion discussion topic for the original entry at http://iq.opengenus.org/types-of-neural-network-optimizations/