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    Recommendation Engines (The MIT Press Essential Knowledge series)

    Beschreibung Recommendation Engines (The MIT Press Essential Knowledge series). How companies like Amazon and Netflix know what “you might also like”: the history, technology, business, and social impact of online recommendation engines.Increasingly, our technologies are giving us better, faster, smarter, and more personal advice than our own families and best friends. Amazon already knows what kind of books and household goods you like and is more than eager to recommend more; YouTube and TikTok always have another video lined up to show you; Netflix has crunched the numbers of your viewing habits to suggest whole genres that you would enjoy. In this volume in the MIT Press's Essential Knowledge series, innovation expert Michael Schrage explains the origins, technologies, business applications, and increasing societal impact of recommendation engines, the systems that allow companies worldwide to know what products, services, and experiences “you might also like.”Schrage offers a history of recommendation that reaches back to antiquity's oracles and astrologers; recounts the academic origins and commercial evolution of recommendation engines; explains how these systems work, discussing key mathematical insights, including the impact of machine learning and deep learning algorithms; and highlights user experience design challenges. He offers brief but incisive case studies of the digital music service Spotify; ByteDance, the owner of TikTok; and the online personal stylist Stitch Fix. Finally, Schrage considers the future of technological recommenders: Will they leave us disappointed and dependent—or will they help us discover the world and ourselves in novel and serendipitous ways?



    Buch Recommendation Engines (The MIT Press Essential Knowledge series) PDF ePub

    Recommendation Engines / The MIT Press ~ In this volume in the MIT Press's Essential Knowledge series, innovation expert Michael Schrage explains the origins, technologies, business applications, and increasing societal impact of recommendation engines, the systems that allow companies worldwide to know what products, services, and experiences “you might also like.”Schrage offers a history of recommendation that reaches back to antiquity's oracles and astrologers; recounts the academic origins and commercial evolution of .

    The MIT Press Essential Knowledge series / The MIT Press ~ The MIT Press Essential Knowledge series offers accessible, concise, beautifully produced books on topics of current interest. Written by leading thinkers, the books in this series deliver expert overviews of subjects that range from the cultural and the historical to the scientific and the technical. In today's era of instant information gratification, we have ready access to opinions .

    Recommendation Engines (The MIT Press Essential Knowledge ~ Michael Schrage at MIT’s Sloan School of Management’s Initiative on the Digital Economy has written a definitive book about recommendation engines, entitled Recommendation Engines. This is a highly recommended and unique book that is readily accessible to technologists, business leaders and the general public. The book is part of MIT’s essential knowledge series which seeks to provide “foundational knowledge that informs a principles understanding of the world.” That sounds a .

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    The MIT Press ~ Recommendation Engines How companies like and Netflix know what “you might also like”: the history, technology, business, and social impact of online recommendation engines. Learn more. By Panos Louridas Algorithms An accessible introduction to algorithms, explaining not just what they are but how they work, with examples from a wide range of application areas. Learn more. By Chad .

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    : Recommender Systems: The Textbook eBook ~ It goes deep into the essential algorithms and mathematics that power recommendation engines and elucidates many concepts that are very hard to grasp by reading other sources. It gives you enough information to know what to look for when using a third party tool or framework. This is essential reading for anyone who wants to build a custom recommendation engine and actually understand how it .

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