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PREDICTIVE LEARNING INDICATOR TEST SAMPLE QUESTIONS New Book

  • An Introduction to Statistical Learning

    An Introduction to Statistical Learning
    Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani

    This book presents some of the most important modeling and prediction techniques, along with relevant applications.

  • Python Machine Learning

    Python Machine Learning
    Sebastian Raschka

    Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn …

  • 5 lb. Book of GRE Practice Problems

    5 lb. Book of GRE Practice Problems
    Manhattan Prep

    Purchase of this book includes access to an online video introduction, online banks of GRE practice problems, and the GRE Challenge Problem Archive.

  • Fundamentals of Machine Learning for Predictive Data Analytics

    Fundamentals of Machine Learning for Predictive Data Analytics
    John D. Kelleher, Brian Mac Namee, Aoife D’Arcy

    A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

  • The Elements of Statistical Learning

    The Elements of Statistical Learning
    Trevor Hastie, Robert Tibshirani, Jerome Friedman

    Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework.

  • Predictive Analytics

    Predictive Analytics
    Eric Siegel

    How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood.

  • Helping Children Succeed

    Helping Children Succeed
    Paul Tough

    Now, in Helping Children Succeed, Tough takes on a new set of pressing questions: What does growing up in poverty do to children’s mental and physical development?

  • Introduction to Statistical Machine Learning

    Introduction to Statistical Machine Learning
    Masashi Sugiyama

    Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice.

  • Bayesian Networks

    Bayesian Networks
    Marco Scutari, Jean-Baptiste Denis

    Suitable for graduate students and non-statisticians, this text provides an introductory overview of Bayesian networks. It gives readers a clear, practical understanding of the general approach and steps involved.

  • Practical Predictive Analytics and Decisioning Systems for Medicine

    Practical Predictive Analytics and Decisioning Systems for Medicine
    Linda Miner, Pat Bolding, Joseph Hilbe, Mitchell Goldstein, Thomas Hill, Robert Nisbet, Nephi Walton, Gary Miner

    Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner.

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