Neural Architecture Search (NAS)

In this section

• Bayesian Optimization: Probabilistic Performance Modeling for Neural Networks
  Bayesian Optimization is a strategy for the probabilistic modeling of neural network performance, widely used in directed architecture search.
• Random Search: Exploring Neural Network Architectures Randomly
  Random Search is a method for exploring neural network architectures by selecting configurations randomly. This article discusses its implementation, benefits, trade-offs, use cases, and provides examples in various programming languages.
• Reinforcement Learning for Neural Architecture Search: Optimal Architectures Exploration
  Explore the use of Reinforcement Learning (RL) to efficiently and effectively discover optimal neural network architectures.