What is model pruning in AI?

What is model pruning in AI?

Model pruning is a technique used to reduce the size of a neural network by removing weights that are deemed unnecessary.

Why is model pruning important?

It's important because it helps improve the efficiency of models, making them faster and less resource-intensive.

How does model pruning affect accuracy?

If done correctly, model pruning can maintain or even improve accuracy while reducing the model size.

What are the different methods of model pruning?

Common methods include weight pruning, neuron pruning, and structured pruning, each with its own advantages.

Can you give an example of model pruning in practice?

Sure! For instance, pruning can be applied to a convolutional neural network to reduce its parameters while maintaining performance.