Practical Automated Machine Learning Using H2O.ai

Discover the power of automated machine learning,from experimentation through to deployment to production

Salil Ajgaonkar

BIRMINGHAM—MUMBAI

Practical Automated Machine Learning Using H2O.ai
Copyright © 2022 Packt Publishing

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First published: September 2022

Production reference: 1140922

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ISBN 978-1-80107-452-0

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Contributors

About the author

Salil Ajgaonkar is a software engineer experienced in building and scaling cloud-based microservices and productizing machine learning models. His background includes work in transaction systems, artificial intelligence, and cyber security. He is passionate about solving complex scaling problems, building machine learning pipelines, and data engineering. Salil earned his degree in IT from Xavier Institute of Engineering, Mumbai, India, in 2015 and later earned his master’s degree in computer science from Trinity College Dublin, Ireland, in 2018, specializing in future networked systems. His work history includes the likes of BookMyShow, Genesys, and Vectra AI.

I would like to thank my lovely wife, Oshin, for supporting me and making sure I gave my best effort to writing this book. Also, thanks to my parents, who taught me to always say “yes” to all opportunities that come my way.

I would also like to thank the Packt team for giving me the opportunity to write this book and play my part in giving back to the programming community. Special thanks to Dhruv for coordinating the publication effort, Kirti for scheduling and keeping things on track over the year, and Nathanya and the editorial team for ensuring that the book is of the highest quality.

Last but not least, special thanks to Dr. Emir Muñoz for his valuable insights into the technical aspects of the book.

About the reviewer

Emir Muñoz is a senior manager of machine learning at Genesys, where he works on projects to enhance customer experience using artificial intelligence, machine learning, and data science. He has experience in academia and industry, which he uses to leverage emerging technologies and algorithms to deliver innovative solutions. Currently, he leads a team that mines contact center data to train machine learning models to optimize contact center routing.

Emir holds a PhD in computer science with a specialization in machine learning. He also received a BEng in informatics and an MSc in computer engineering. He is the author of several papers and patents on the topics of semantic web, machine learning, knowledge graphs, and contact center analytics.