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  1. Multivariate Statistical Machine Learning Methods for Genomic... - 9783030890094

    ISBN-13: 9783030890094, 978-3030890094. Lastly, worked-out examples help readers check their own [url] book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool.

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  2. Pattern Recognition and Machine Learning by Christopher M. Bishop New Stock

    NOTE: - IMAGES ARE FOR ILLUSTRATIONS ONLY.

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  3. Machine Learning : A Probabilistic Perspective by Kevin P. Murphy (2012 Hardback

    Machine Learning : A Probabilistic Perspective by Kevin P. Murphy (2012, Hardcover) - Adaptive Computation and Machine Learning Ser. The publication year was auto-generated from the ISBN of the book and may not match this copy.

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  4. Mathematical Analysis for Machine Learning & Data Mining–D. Simovici (Hardcover)

    This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book. (Hardcover) New Condition!! (Last copy available)

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  5. Machine Learning with R - Second Edition by Brett Lantz (2015, Trade Paperback)

    The "Machine Learning with R - Second Edition" by Brett Lantz is a comprehensive textbook written in English, focusing on the subject area of computers. Published by Packt Publishing, The Limited in 2015, this trade paperback covers topics related to programming languages, machine theory, algorithms, and mathematical and statistical software. With a total of 452 pages, this book provides in-depth guidance for those looking to enhance their understanding and skills in machine learning with R.

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  6. Bioinformatics – The Machine Learning..., Bach, Francis

    Bioinformatics – The Machine Learning Approach 2e. Author:Bach, Francis. Publisher:MIT Press Ltd. Book Binding:Hardback. A new book will be sold once but their stories can be enjoyed by more than one owner.

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  7. Machine Learning for Text-Charu C. Aggarwal

    Author: Charu C. Aggarwal ISBN 10: 3319735306. Title: Machine Learning for Text Item Condition: used item in a very good condition. Binding: Hardcover Language: english. Publisher: Springer ISBN 13: 9783319735306.

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  8. Machine Learning: a Probabilistic Perspective (Adaptive Computation and machine

    Anaira Enterprises — Machine Learning textbook by Kevin P. Murphy (author: Senior Staff Research Scientist)Comprehensive probabilistic introduction using probabilistic models and inferenceIncludes PMTK MATLAB code and examples; PMTK (probabilistic modeling toolkit) freely available onlineCovers probability, optimization, and linear algebra plus conditional random fields, L1 regularization, and deep learningInformal, accessible style with pseudo-code, color images, and copious worked examplesWorked examples drawn from biology, text processing, computer vision, and robotics.

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