The overwhelming data produced everyday and the increasing performance and cost requirements of applications are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data.
This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a.
Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data) book series pdf
download Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data) pdf free
Noel Lopes, Bernardete Ribeiro ebooks downloads
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