Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Paperback. Condition: new. Paperback. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions.Comprising a broad overview of how to design machine learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models.From choosing the right hardware to designing effective pipelines architectures and adopting software development best practices, this guide will appeal to machine learning and data science specialists, whilst also laying out key high-level principlesin a way that is approachable for students of computer science and aspiring programmers. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a disparity. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Taylor & Francis Ltd, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Chapman and Hall/CRC, 2025
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Chapman and Hall/CRC 2025-04-01, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Published by Taylor and Francis Ltd, GB, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Add to basketPaperback. Condition: New. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions.Comprising a broad overview of how to design machine learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models.From choosing the right hardware to designing effective pipelines architectures and adopting software development best practices, this guide will appeal to machine learning and data science specialists, whilst also laying out key high-level principlesin a way that is approachable for students of computer science and aspiring programmers.
Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Published by Chapman and Hall/CRC, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
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Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Add to basketPaperback. Condition: new. Paperback. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions.Comprising a broad overview of how to design machine learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models.From choosing the right hardware to designing effective pipelines architectures and adopting software development best practices, this guide will appeal to machine learning and data science specialists, whilst also laying out key high-level principlesin a way that is approachable for students of computer science and aspiring programmers. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a disparity. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketPaperback. Condition: Brand New. 346 pages. 9.19x6.13x9.21 inches. In Stock.
Published by Taylor & Francis Ltd Apr 2025, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware - Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a disparity.
Published by Taylor & Francis Ltd, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Language: English
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Published by Chapman and Hall/CRC, 2023
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Language: English
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Published by Chapman and Hall/CRC 2023-03-31, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Language: English
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Language: English
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Published by Taylor & Francis Ltd, London, 2025
ISBN 10: 0367255065 ISBN 13: 9780367255060
Language: English
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Add to basketPaperback. Condition: new. Paperback. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions.Comprising a broad overview of how to design machine learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models.From choosing the right hardware to designing effective pipelines architectures and adopting software development best practices, this guide will appeal to machine learning and data science specialists, whilst also laying out key high-level principlesin a way that is approachable for students of computer science and aspiring programmers. Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a disparity. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Chapman and Hall/CRC, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Language: English
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