Call to action – where do I go next?

All good things must end, and so does this book. Whew! We covered a lot of ground here. Automated ML is an active area of research and development, and in this book, we tried to give you a breadth-first overview of the fundamentals, key benefits, and platforms. We explained the underlying techniques of automated feature engineering, model and hyperparameter learning, and neural architecture search with examples from open source toolkits and cloud platforms. We covered a detailed walkthrough of three major cloud platforms, namely Microsoft Azure, AWS, and GCP. With the step-by-step walkthroughs, you saw the automated ML feature set offered in each platform by building ML models and trying them out.

The learning journey does not end here. There are several great references provided in the book where you can further do a deep dive to learn more about the topic. Automated ML platforms, especially cloud platforms, are always in flux, so by...