What is Model Optimization?

Model optimization refers to techniques and processes used to improve the performance of machine learning models. This can involve reducing the model's size (making it more efficient to store and deploy), increasing its speed (reducing latency in predictions), or improving its accuracy (generalization to unseen data). Common methods include quantization, pruning, knowledge distillation, and architecture search.