Chapter 3: Automated Machine Learning with Open Source Tools and Libraries

"Empowerment of individuals is a key part of what makes open source work since, in the end, innovations tend to come from small groups, not from large, structured efforts."

– Tim O'Reilly

"In open source, we feel strongly that to really do something well, you have to get a lot of people involved."

– Linus Torvalds

In the previous chapter, you looked under the hood of automated Machine Learning (ML) technologies, techniques, and tools. You learned how AutoML actually works – that is, the algorithms and techniques of automated feature engineering, automated model and hyperparameter turning, and automated deep learning. You also explored Bayesian optimization, reinforcement learning, the evolutionary algorithm, and various gradient-based approaches by looking at their use in automated ML.

However, as a hands-on engineer, you probably don't get the...