Description

The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.

Elements of Data Science, Machine Learning, and Artificial Intelligence Using R

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£54.99

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Hardback by Frank Emmert-Streib , Salissou Moutari

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The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and... Read more

    Publisher: Springer International Publishing AG
    Publication Date: 04/10/2023
    ISBN13: 9783031133381, 978-3031133381
    ISBN10: 3031133382

    Number of Pages: 575

    Non Fiction , Technology, Engineering & Agriculture , Education

    Description

    The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.

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