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.
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Matthias Bannert, Ph.D. gained his hands-on data science and data engineering at ETH Zürich 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 section lead in the innovation-minded KOF Lab. In 2021, he was a co-chair of useR!, the annual user conference of the R Project for Statistical Computing. He remains an active contributor to extension packages of the R language and the open source community in general.
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Paperback. Etat : 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. N° de réf. du vendeur 9781032261270
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Paperback. Etat : New. 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. N° de réf. du vendeur LU-9781032261270
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