Ciaburro Giuseppe - Python Machine Learning Cookbook

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First published: June 2016
Second edition: March 2019

Production reference: 1290319

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ISBN 978-1-78980-845-2

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Giuseppe Ciaburro holds a PhD in environmental technical physics, along with two master's degrees. His research was focused on machine learning applications in the study of urban sound environments. He works at the Built Environment Control Laboratory at the Universit degli Studi della Campania Luigi Vanvitelli, Italy. He has over 15 years' professional experience in programming (Python, R, and MATLAB), first in the field of combustion, and then in acoustics and noise control. He has several publications to his credit.

Prateek Joshi is an artificial intelligence researcher, an author of several books, and a TEDx speaker. He has been featured in Forbes 30 Under 30, CNBC, TechCrunch, Silicon Valley Business Journal, and many more publications. He is the founder of Pluto AI, a venture-funded Silicon Valley start-up building an intelligence platform for water facilities. He graduated from the University of Southern California with a Master's degree specializing in Artificial Intelligence. He has previously worked at NVIDIA and Microsoft Research.

Greg Walters has been involved with computers and computer programming since 1972 . Currently, he is extremely well versed in Visual Basic, Visual Basic .NET, Python, and SQL using MySQL, SQLite, Microsoft SQL Server, Oracle, C++, Delphi, Modula-2, Pascal, C, 80x86 Assembler, COBOL, and Fortran.

He is a programming trainer and has trained numerous people in many pieces of computer software, including MySQL, Open Database Connectivity, Quattro Pro, Corel Draw!, Paradox, Microsoft Word, Excel, DOS, Windows 3.11, Windows for Workgroups, Windows 95, Windows NT, Windows 2000, Windows XP, and Linux.

He is currently retired, and, in his spare time, is a musician and loves to cook, but he is also open to working as a freelancer on various projects.

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This eagerly anticipated second edition of the popular Python Machine Learning Cookbook, Second Edition, will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.

With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With an emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques for fields including reinforcement learning, deep neural networks, and automated machine learning.

By the end of this book, you will be equipped, through real-world examples, with the skills you need to apply machine learning techniques, and will be able to leverage the full capabilities of the Python ecosystem.

This book is for data scientists, machine learning developers, deep learning enthusiasts, and Python programmers who want to solve real-world challenges using machine learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in the machine learning and deep learning domains, then this book is what you need.