Springer - Encyclopedia Of Machine Learning And Data Mining, 2nd Edition (2017 EN)

Discussion in 'Artificial intelligence 0' started by Kanka, Oct 31, 2019.

  1. Kanka

    Kanka Well-Known Member Loyal User

    Likes Received:
    Trophy Points:

    Author: Claude Sammut (Editor), Geoffrey I. Webb (Editor)
    Full Title: Encyclopedia Of Machine Learning And Data Mining, 2nd Edition
    Publisher: Springer; 2nd ed. 2017 edition (March 15, 2017)
    Year: 2017
    ISBN-13: 9781489976871 (978-1-4899-7687-1), 9781489976857 (978-1-4899-7685-7), 9781489976864 (978-1-4899-7686-4)
    ISBN-10: 1489976876, 148997685X, 1489976868
    Pages: 1335
    Language: English
    Genre: Educational: Artificial Intelligence
    File type: EPUB (True), PDF (True)
    Quality: 10/10
    Price: 713.99 €

    This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. A paramount work, its 800 entries - about 150 of them newly updated or added - are filled with valuable literature references, providing the reader with a portal to more detailed information on any given topic.Topics for the Encyclopedia of Machine Learning and Data Mining include Learning and Logic, Data Mining, Applications, Text Mining, Statistical Learning, Reinforcement Learning, Pattern Mining, Graph Mining, Relational Mining, Evolutionary Computation, Information Theory, Behavior Cloning, and many others. Topics were selected by a distinguished international advisory board. Each peer-reviewed, highly-structured entry includes a definition, key words, an illustration, applications, a bibliography, and links to related literature.The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals who employ machine learning and data mining methods in their projects. Machine learning and data mining techniques have countless applications, including data science applications, and this reference is essential for anyone seeking quick access to vital information on the topic.


Share This Page