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Machine Learning for Adaptive Many-Core Machines - A Practical Approach

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  • 264 pages
  • 10 hours of reading

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The book explores the challenges posed by the vast amounts of data generated daily and the growing demands on applications across various sectors, including science and industry. It emphasizes the necessity for adaptive many-core machines capable of efficiently scaling to manage the complexity and volume of tasks required by Machine Learning algorithms, addressing the critical intersection of technology and Big Data.

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Machine Learning for Adaptive Many-Core Machines - A Practical Approach, Noel Lopes, Bernardete Ribeiro

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2016
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