Neural Architecture Search: Automating the Design of Artificial Neural Networks

Designing an effective neural network architecture has traditionally required deep expertise, trial-and-error experimentation, and significant time investment. Data scientists often spend weeks fine-tuning layers, parameters, and configurations to achieve optimal performance. Neural Architecture Search (NAS) addresses this challenge by automating the process of designing neural networks. It uses algorithms to explore a vast space of…