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Real-World Machine Learning
Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution.
Real-World Machine Learning
Item #: 3695470

Real-World Machine Learning

Item #: 3695470

AED 215

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    Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution.
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    What Stands Out

    Practical Applications
    Focuses on real-world applications of machine learning, providing hands-on examples that enhance understanding and retention, making it ideal for practitioners and students aiming to implement ML solutions effectively.
    Comprehensive Coverage
    Covers a wide range of machine learning techniques and algorithms, ensuring readers gain a thorough understanding of both foundational concepts and advanced topics, leading to well-rounded expertise in the field.
    Accessible Learning
    Designed for varied skill levels, the book employs clear explanations and practical exercises, making machine learning accessible to beginners while still offering valuable insights for more experienced learners.

    Product Details

    Shop now for Real-World Machine Learning First Edition at Ubuy UAE. Discover the best prices and deals on machine learning books. Don't miss out!
    • Practical guide for working developers to execute ML projects without overwhelming academic theory and complex mathematics
    • Introduces day-to-day practice of machine learning to successfully build and deploy powerful ML systems
    • Purchase includes free eBook in PDF, Kindle, and ePub formats from Manning Publications
    • Teaches concepts and techniques needed without overdosing on abstract theory and complex mathematics
    • Covers immediately relevant examples in Python, including data acquisition, modeling, classification, and regression
    • Helps readers develop skills in model validation, optimization, scalability, and real-time streaming
    Publisher Manning
    Publication date September 30, 2016
    Edition First Edition
    Language English
    Print length 264 pages
    ISBN-10 9781617291920
    ISBN-13 978-1617291920
    Item Weight 1 pounds (450 grams)
    Dimensions 7.38 x 0.5 x 9.25 inches (18.7 x 1.3 x 23.5 cm)

    Who Should Buy?

    Suitable For
    • Aspiring Data Scientists

      Provides practical insights and hands-on examples to help beginners start their journey in machine learning.

    • Industry Professionals

      Useful for professionals looking to apply machine learning techniques in real-world applications across various industries.

    • Academic Learners

      Designed for students seeking to understand the practicalities of machine learning beyond theoretical foundations.

    Not Suitable For
    • Complete Beginners

      Those with no prior knowledge of programming or statistics may find it challenging to grasp the content.

    Product Description

    Real-World Machine Learning

    About This Item

    Introducing the Real-World Machine Learning First Edition Book Are you ready to take your machine learning skills to the next level and apply them to real-world applications? Look no further than the Real-World Machine Learning First Edition book. Whether you're a beginner or an experienced practitioner, this book will provide you with the knowledge and techniques needed to implement machine learning in practical scenarios. Inside this book, you'll find a comprehensive guide filled with real-life examples and case studies showcasing the power of machine learning in various industries. From finance to healthcare, marketing to transportation, this book covers it all. Learn how to analyze real-world data sets and uncover valuable insights using machine learning algorithms.

    Discover best practices for implementing machine learning models and techniques for overcoming common challenges. Gain a deep understanding of the latest advancements and strategies in the field of machine learning. With the Real-World Machine Learning First Edition book, you'll have everything you need to excel in the world of machine learning. Whether you're a student, a data scientist, or a business professional, this book is a must-have resource for anyone looking to harness the power of machine learning in their daily work. Don't miss out on this opportunity to expand your machine learning skills and stay ahead of the competition.

    Order your copy of the Real-World Machine Learning First Edition book today and unlock the potential of machine learning in the real world.

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    Software Development Editorial Review

    Real-World Machine Learning is a well-organized and presented book that is useful for anyone learning about machine learning, providing a cohesive approach for explaining and illustrating the practical steps involved in building and evaluating models. Although some reviewers warn it is not an introductory book and is too skimpy on mathematical details, it provides great project ideas and code examples for feature engineering and scaling of machine learning systems. The book is aimed at intermediate-level developers with prior basic familiarity with Python coding and algorithms, making it a useful companion for programmers wanting to adopt machine learning practices. The strengths of the book are in its coverage of feature engineering and scaling of machine learning systems. One weakness highlighted is its presentation of figures in black-and-white, making them less useful, but the color figures are available in the easy-to-access PDF version. Overall, it is a highly readable, practical book that addresses all real-life issues in machine learning.

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    Pros

    • Well-organized and presented
    • Good systematic approach for explaining and illustrating practical steps
    • Good project ideas and code examples for feature engineering and scaling of machine learning systems
    • Useful for anyone learning about machine learning
    • No mathematical background required
    • No prior familiarity with various types of statistical models used in ML necessary
    • Strengths in coverage of feature engineering and scaling of machine learning systems
    • Authors demonstrate hands-on knowledge of the subject
    • Example Notebooks and associated data available for download

    Cons

    • Not an introductory book

    Product Price History

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