Artificial Intelligence & Machine Learning
Neural Architecture Search (NAS)
Definition
Neural Architecture Search (NAS) is a technique for automating the design of artificial neural networks. NAS uses a machine learning algorithm to search for the best neural network architecture for a given task.
Why It Matters
Designing high-performing neural network architectures is a complex and time-consuming process that requires significant human expertise. NAS automates this process, potentially discovering architectures that are more efficient and performant than human-designed ones.
Contextual Example
A NAS algorithm could automatically experiment with different numbers of layers, types of layers, and connections to find the optimal architecture for an image classification problem.
Common Misunderstandings
- NAS is computationally very expensive, as it involves training and evaluating many different network architectures.
- It is a form of "AutoML" (Automated Machine Learning).