Practical machine learning with Python : a problem-solver's guide to building real-world intelligent systems / Dipanjan Sarkar, Raghav Bali, Tushar Sharma.

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Practical machine learning with Python : a problem-solver's guide to building real-world intelligent systems / Dipanjan Sarkar, Raghav Bali, Tushar Sharma.

9781484232071 (electronic book)
1484232070 (electronic book)
9781484232064
1484232062

[United States] : Apress, 2018.

New York, NY : Distributed to the Book trade worldwide by Springer

©2018

English

1 online resource

10.1007/978-1-4842-3207-1 doi

Q325.5

006.3/1

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! You will: Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering.

Includes index.

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Online resource; title from PDF title page (SpringerLink, viewed January 9, 2018).

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