Evolutionary Methods and AutoML Zero

This chapter explores the advantages of using evolutionary methods over traditional reinforcement learning for optimizing machine learning models, particularly in tasks such as computer vision. It dives into the innovative AutoML Zero project, which automates the creation of machine learning algorithms from basic operations, uncovering novel techniques and architectures throughout its evolutionary process. Additionally, the chapter addresses challenges in scaling these approaches to complex datasets and the significance of advanced normalization techniques in enhancing neural network performance.