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Principes fondamentaux de l'apprentissage automatique pour l'analyse prédictive des données : algorithmes, travail
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Principes fondamentaux de l'apprentissage automatique pour l'analyse prédictive des données : algorithmes, travail
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Principes fondamentaux de l'apprentissage automatique pour l'analyse prédictive des données : algorithmes, travail

14,96 $US
Environ20,61 $C
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    Expédition :
    6,72 $US (environ 9,26 $C) USPS Media MailTM.
    Lieu : Dublin, California, États-Unis
    Livraison :
    Livraison prévue entre le jeu. 7 août et le lun. 11 août à 94104
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    Numéro de l'objet eBay :205600844551
    Dernière mise à jour : juil. 06, 2025 16:59:38 HAEAfficher toutes les modificationsAfficher toutes les modifications

    Caractéristiques de l'objet

    État
    Acceptable: Un livre présentant des traces d'usure apparentes. Sa couverture peut être endommagée, ...
    Book Title
    Fundamentals of Machine Learning for Predictive Data Analytics: A
    Narrative Type
    Nonfiction
    Genre
    Specialty Boutique
    Topic
    Internet & Social Media
    Intended Audience
    Adult
    Inscribed
    NO
    ISBN
    9780262029445

    À propos de ce produit

    Product Identifiers

    Publisher
    MIT Press
    ISBN-10
    0262029448
    ISBN-13
    9780262029445
    eBay Product ID (ePID)
    208620163

    Product Key Features

    Number of Pages
    624 Pages
    Publication Name
    Fundamentals of Machine Learning for Predictive Data Analytics : Algorithms, Worked Examples, and Case Studies
    Language
    English
    Subject
    Probability & Statistics / Stochastic Processes, Intelligence (Ai) & Semantics, Databases / Data Mining
    Publication Year
    2015
    Type
    Textbook
    Subject Area
    Mathematics, Computers
    Author
    Aoife D'arcy, Brian Mac Namee, John D. Kelleher
    Format
    Hardcover

    Dimensions

    Item Height
    1.1 in
    Item Weight
    36.5 Oz
    Item Length
    9.2 in
    Item Width
    7.3 in

    Additional Product Features

    Intended Audience
    Trade
    LCCN
    2014-046123
    Dewey Edition
    23
    Illustrated
    Yes
    Dewey Decimal
    006.3/1
    Synopsis
    A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals., A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning- information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
    LC Classification Number
    Q325.5.K455 2015

    Description de l'objet du vendeur

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    nerdssavetheworld

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      Very happy with this purchase! The packaging was great, and the value was well worth the price. Shipping was fast. Just as the listing described.
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      Fast shipping. Great protective packaging. Came as described (perfect). Would definitely buy again from this seller!
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      Thank you again.. love doing business with this seller.. they are awesome & responsive & fast shipping & very fair shipping price. I’ve done business twice & will again hopefully in the future.. they deserve 10 stars but since I can’t then I’ll say A+++++++++++++ Thank you to the seller & to any potential buyers that read this, don’t hesitate bc you are in good hands & they definitely package the items very, very well..