Learning Path

Deep Learning Fundamentals → Evaluation and Comparison of NAS Methods

This advanced graduate-level path teaches the core algorithmic paradigms for automating neural network design: reinforcement learning-based search, evolutionary methods, differentiable search, and hyperparameter optimization. It builds from deep learning and optimization prerequisites through the foundational concepts and mathematical machinery to a critical understanding of NAS algorithms.