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Practical machine learning with Python : a problem-solver's guide to building real-world intelligent systems

Author: Dipanjan Sarkar; Raghav Bali; Tushar Sharma
Publisher: [Berkeley, California] : Apress, New York, NY : Distributed to the book trade worldwide by Springer [2018] ©2018
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"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  Read more...
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Document Type: Book
All Authors / Contributors: Dipanjan Sarkar; Raghav Bali; Tushar Sharma
ISBN: 1484232062 9781484232064
OCLC Number: 1005116362
Notes: Includes index.
Description: xxv, 530 pages : illustrations ; 26 cm
Contents: Introduction --
Part 1. Understanding machine learning. Machine learning basics --
The Python machine learning ecosystem --
Part 2. The machine learning pipeline. Processing, wrangling, and visualizing data --
Feature engineering and selection --
Building, tuning, and deploying models --
Part 3. Real-world case studies. Analyzing bike sharing trends --
Analyzing movie reviews sentiment --
Customer segmentation and effective cross selling --
Analyzing wine types and quality --
Analyzing music trends and recommendations --
Forecasting stock and commodity prices --
Deep learning for computer vision.
Responsibility: Dipanjan Sarkar, Raghav Bali, Tushar Sharma.

Abstract:

"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. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today"--Provided by publisher.

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