Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Add to basketCondition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Paperback. Condition: new. Paperback. Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Featuresoverview: breakdown of complex data science software stacks into core componentsapplied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source softwarereader guidance: different entry points and rich references to deepen the understanding of selected aspects Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Taylor & Francis Ltd Apr 2024, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
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Add to basketTaschenbuch. Condition: Neu. Neuware - Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
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Add to basketCondition: New. Matthias Bannert, Ph.D. gained his hands-on data science and data engineering at ETH Zuerich in more than a decade of working for the KOF Swiss Economic Institute. Today, he works as a data engineering expert advisor at cynkra and supports ETH as a.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Add to basketPaperback. Condition: new. Paperback. Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Featuresoverview: breakdown of complex data science software stacks into core componentsapplied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source softwarereader guidance: different entry points and rich references to deepen the understanding of selected aspects Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261277 ISBN 13: 9781032261270
Language: English
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Add to basketPaperback. Condition: new. Paperback. Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Featuresoverview: breakdown of complex data science software stacks into core componentsapplied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source softwarereader guidance: different entry points and rich references to deepen the understanding of selected aspects Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
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ISBN 10: 1032261641 ISBN 13: 9781032261645
Language: English
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Published by Chapman and Hall/CRC, 2024
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Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
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Hardcover. Condition: new. Hardcover. Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Featuresoverview: breakdown of complex data science software stacks into core componentsapplied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source softwarereader guidance: different entry points and rich references to deepen the understanding of selected aspects Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032261641 ISBN 13: 9781032261645
Language: English
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Add to basketHardcover. Condition: new. Hardcover. Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Featuresoverview: breakdown of complex data science software stacks into core componentsapplied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source softwarereader guidance: different entry points and rich references to deepen the understanding of selected aspects Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.