Description

Book Synopsis

The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field.

It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application domains. It demonstrates the fundamental techniques involved in data collection, integration, cleansing, transformation, development, and deployment of machine learning models. This book emphasizes the importance of integrating responsible and explainable AI into machine learning models, ensuring these principles are prioritized rather than treated as an afterthought. To support learning, this book also offers information on accessing additional machine learning resources such as datasets, libraries, pre-trained models, and tools for tracking machine learning models.

This is a core resource for students and instructors of machine learning and data science looking for beginner-

Practical Machine Learning

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Order before 4pm today for delivery by Tue 13 Jan 2026.

A Paperback by Ally S. Nyamawe

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    View other formats and editions of Practical Machine Learning by Ally S. Nyamawe

    Publisher: CRC Press
    Publication Date: 1/30/2025
    ISBN13: 9781032770291, 978-1032770291
    ISBN10: 1032770295

    Description

    Book Synopsis

    The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field.

    It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application domains. It demonstrates the fundamental techniques involved in data collection, integration, cleansing, transformation, development, and deployment of machine learning models. This book emphasizes the importance of integrating responsible and explainable AI into machine learning models, ensuring these principles are prioritized rather than treated as an afterthought. To support learning, this book also offers information on accessing additional machine learning resources such as datasets, libraries, pre-trained models, and tools for tracking machine learning models.

    This is a core resource for students and instructors of machine learning and data science looking for beginner-

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