Neural Architecture Search (NAS)
- is a technique in AutoML that automates the design of artificial neural network architectures for specific tasks, often surpassing manually designed models in performance
- focuses on optimizing the topology of neural networks, including layer types, connections, and operations, to achieve desired metrics such as accuracy, model size, or inference speed