Deep Learning

Model Pruning

Removing unimportant parameters or structures from a neural network.

Model pruning identifies weights, neurons, attention heads or layers that contribute little to performance. These components can be removed to create a smaller and faster network.

Pruning may be performed gradually during training or after the model has been trained. The pruned model is often fine-tuned to recover any accuracy lost during compression.

Also in Deep Learning

CNN RNN LSTM Transformers Auto Encoders Deep RL

JOIN NOW

Begin the first module

It is free, it is the real curriculum, and if it is not for you, you have lost nothing but an evening.

See the curriculum

Join any time · Build AI skills at your pace