Python Machine Learning
Third Edition
Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
Sebastian Raschka
Vahid Mirjalili
BIRMINGHAM - MUMBAI
Python Machine Learning
Third Edition
Copyright © 2019 Packt Publishing
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First published: September 2015
Second edition: September 2017
Third edition: November 2019
Production reference: 1091219
Published by Packt Publishing Ltd.
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ISBN 978-1-78995-575-0
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Contributors
About the authors
Sebastian Raschka received his doctorate from Michigan State University, where he focused on developing methods at the intersection of computational biology and machine learning. In the summer of 2018, he joined the University of Wisconsin-Madison as Assistant Professor of Statistics. His research activities include the development of new deep learning architectures to solve problems in the field of biometrics.
Sebastian has many years of experience with coding in Python and has given several seminars on the practical applications of data science, machine learning, and deep learning over the years, including a machine learning tutorial at SciPy, the leading conference for scientific computing in Python.
Among Sebastian's achievements is his book Python Machine Learning, which is a bestselling title at Packt and on Amazon.com. The book received the ACM Best of Computing award in 2016 and was translated into many different languages, including German, Korean, Chinese, Japanese, Russian, Polish, and Italian.
In his free time, Sebastian loves to contribute to open source projects, and methods that he implemented are now successfully used in machine learning competitions such as Kaggle.
I would like to take this opportunity to thank the great Python community and the developers of open source packages who helped me create the perfect environment for scientific research and data science. Also, I want to thank my parents, who always encouraged and supported me in pursuing the path and career that I was so passionate about.
Special thanks to the core developers of scikit-learn and TensorFlow. As a contributor and user, I had the pleasure of working with great people who are not only very knowledgeable when it comes to machine learning and deep learning but are also excellent programmers.
Vahid Mirjalili obtained his PhD in mechanical engineering working on novel methods for large-scale, computational simulations of molecular structures at Michigan State University. Being passionate about the field of machine learning, he joined the iPRoBe lab at Michigan State University, where he worked on applying machine learning in the computer vision and biometrics domains. After several productive years at the iPRoBe lab and many years in academia, Vahid recently joined 3M Company as a research scientist, where he can use his expertise and apply state-of-the-art machine learning and deep learning techniques to solve real-world problems in various applications to make life better.
I would like to thank my wife, Taban Eslami, who has been very supportive and encouraged me on my career path. Also, special thanks to my advisors, Nikolai Priezjev, Michael Feig, and Arun Ross, for supporting me during my PhD studies, as well as my professors, Vishnu Boddeti, Leslie Kuhn, and Xiaoming Liu, who have taught me so much and encouraged me to pursue my passion.
About the reviewers
Raghav Bali is a senior data scientist at one of the world's largest healthcare organizations. His work involves the research and development of enterprise-level solutions based on machine learning, deep learning, and natural language processing for healthcare- and insurance-related use cases. In his previous role at Intel, he was involved in enabling proactive data-driven IT initiatives using natural language processing, deep learning, and traditional statistical methods. He has also worked in the finance domain with American Express, solving digital engagement and customer retention use cases.
Raghav has also authored multiple books with leading publishers, the most recent being on the latest advancements in transfer learning research.
Raghav has a master's degree (gold medalist) in information technology from the International Institute of Information Technology, Bangalore. Raghav loves reading and is a shutterbug, capturing moments when he isn't busy solving problems.
Motaz Saad holds a PhD in computer science from the University of Lorraine. He loves data and he likes to play with it. He has over 10 years of professional experience in natural language processing, computational linguistics, data science, and machine learning. He currently works as an assistant professor at the faculty of Information Technology, IUG.