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    1. Ekonomi och Ledarskap
    2. Företagsekonomi
    3. Affärsförhandlingar

    Foundations of Programming, Statistics, and Machine Learning for Business Analytics

    AvRam Gopal,Dan Philps

    Inbunden, Engelska, 2023

    3 367 kr

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    Fler format och utgåvor

    Häftad

    733 kr

    Beskrivning

    Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.

    This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. 

    Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.

    Key features:

    ·       Introduces programming fundamentals using R and Python

    ·       Covers data structures, data management and manipulation and data visualization

    ·       Includes interactive coding notebooks so that you can build up your programming skills progressively

    Suitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.

    Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.

    Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.

    Tillman Weyde is Senior Lecturer at City, University of London.

    Produktinformation

    • Utgivningsdatum:2023-04-28
    • Mått:189 x 246 x 32 mm
    • Vikt:1 280 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:512
    • Upplaga:1
    • Förlag:SAGE Publications
    • ISBN:9781529620900

    Utforska kategorier

    • Affärsförhandlingar inom Ekonomi och Ledarskap

    Mer om författaren

    Ram D. Gopal is the Information Systems Society’s Distinguished Fellow and Alan Turing Institute’s Turing Fellow, a Professor of Information Systems and Management, and Pro-Dean for Research, Engagement, and Impact at the Warwick Business School.  Dan Philps is a veteran quantitative investment manager and a widely published artificial intelligence (AI) researcher.  Tillman Weyde is a Reader in Computer Science at City, University of London. Before joining City in 2005, he worked as a researcher in the Research Department for Music and Media Technology at the University of Osnabrück.

    Innehållsförteckning

    • Chapter 1: Introduction To Programming And StatisticsChapter 2: Summarizing And Visualizing DataChapter 3: Summarizing And Visualizing DataChapter 4: Programming FundamentalsChapter 5: Programming FundamentalsChapter 6: DistributionsChapter 7: Statistical Testing – Concepts and StrategyChapter 8: Statistical Testing – Concepts and StrategyChapter 9: Nonparametric TestsChapter 10: Reality CheckChapter 11: Fundamentals of EstimationChapter 12: Linear ModelsChapter 13: General Linear ModelsChapter 14: Regression Diagnostics And StructureChapter 15: Timeseries And ForecastingChapter 16: Introduction To Machine LearningChapter 17: Model Selection And Cross ValidationChapter 18: Regression Models In Machine LearningChapter 19: Classification Models And EvaluationChapter 20: Automated Machine Learning
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