The Hundred-Page Machine Learning Book

The Hundred-Page Machine Learning Book (English, Paperback, Andriy Burkov)

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The Hundred-Page Machine Learning Book  (English, Paperback, Andriy Burkov)

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    Highlights
    • Language: English
    • Binding: Paperback
    • Publisher: Andriy Burkov
    • Genre: Computers
    • ISBN: 9781999579548, 1999579542
    • Edition: 1, 2019
    • Pages: 160
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  • Description
    Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: “Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field.” Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: “The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field.” Karolis Urbonas, Head of Data Science at Amazon: “A great introduction to machine learning from a world-class practitioner.” Sujeet Varakhedi, Head of Engineering at eBay: “Andriy's book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.” Everything you really need to know in Machine Learning in a hundred pages.
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    Specifications
    Book Details
    Publication Year
    • 2019
    Contributors
    Author Info
    • Andriy Burkov is a dad of two and a machine learning expert based in Quebec City, Canada. Nine years ago, he got a Ph.D. in Artificial Intelligence, and for the last six years, he's been leading a team of machine learning developers at Gartner. His specialty is natural language processing. His team works on building state-of-the-art multilingual text extraction and normalization systems for production, using both shallow and deep learning technologies.
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