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Machine Learning: An Applied Mathematics Introduction, (Paperback)
Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics
Machine Learning: An Applied Mathematics Introduction, (Paperback)
Item #: 43340608

Machine Learning: An Applied Mathematics Introduction, (Paperback)

Item #: 43340608

AED 112

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    Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics
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    What Stands Out

    Applied Focus
    This book emphasizes practical applications of machine learning concepts, making it ideal for those looking to implement theory in real-world scenarios.
    Mathematical Foundation
    It uniquely combines machine learning with applied mathematics, ensuring readers build a strong theoretical understanding to enhance their analytical skills in various fields.
    Comprehensive Coverage
    Offers extensive coverage of key algorithms and techniques, enabling a thorough grasp of the subject that caters to both beginners and advanced learners.

    Product Details

    Shop Machine Learning: An Applied Mathematics Introduction, (Paperback) online at a best price in UAE. 809078782
    • Covers essential mathematics behind topics like K Nearest Neighbours, K Means Clustering, Naïve Bayes Classifier, and more
    • Includes real-world examples from fields such as finance, economics, politics, biology, sociology, gambling, and business
    • Authored by Paul Wilmott, who brings three decades of experience in mathematics education
    • Designed as an accessible introduction for those seeking to understand the foundations of machine learning
    • Offers a practical approach for readers who want to grasp the core concepts efficiently
    • Presents an inimitable style of teaching to make the subject engaging and comprehensible
    Book formatPaperback
    Fiction/nonfictionNon-Fiction
    GenreTextbooks
    Publication dateMay, 2019
    Pages242
    SubgenreGeneral
    Series titleNo Series
    Edition1
    PublisherPanda Ohana Publishing
    Original languagesEnglish
    LanguageEnglish
    Edu focusMath & Counting
    Educational levelGeneral
    Is collectibleN
    Binding typePerfect Binding
    Recording time0 min
    Retail packagingSingle Piece
    Assembled product dimensions (l x w x h)6.14 x 0.51 x 9.21 in (15.6 x 1.3 x 23.4 cm)
    Assembled product weight0.76 lb (340 grams)
    Bisac subject headingMathematics

    Who Should Buy?

    Suitable For
    • Mathematics Students

      Ideal for those studying applied mathematics, providing a solid foundation for understanding machine learning concepts.

    • Data Science Beginners

      Perfect for newcomers to data science who need to grasp mathematical principles underpinning machine learning techniques.

    • Professionals in Tech

      Beneficial for tech professionals seeking to enhance their skills in machine learning through an applied mathematics lens.

    Not Suitable For
    • Complete Beginners

      Not suitable for individuals with no prior knowledge of mathematics or machine learning concepts.

    Product Description

    Machine Learning: An Applied Mathematics Introduction, (Paperback)

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    Paul Wilmott All Books Editorial Review

    Machine Learning: An Applied Mathematics Introduction (Paperback) is a comprehensive guide that delves into the mathematical foundations crucial for understanding machine learning concepts. This non-fiction textbook, published in May 2019, spans 242 pages, making it an excellent resource for learners at a general educational level. With a perfect binding format, it's designed for easy handling during study sessions. The book adeptly bridges the gap between mathematics and its application in machine learning, marking it as an essential read. Readers can expect a thorough exploration of math and counting essential for grasping machine learning algorithms and techniques.

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    Pros

    • Accessible for general educational levels
    • Covers essential mathematical concepts
    • Well-structured for easy comprehension
    • Perfect binding ensures durability
    • Lightweight and portable format

    Cons

    • May lack advanced topics for experienced learners

    Product Price History

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