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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    £999.99

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    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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