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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms (Advances in Systems Analysis, Software Engineering, and High Performance Computing)

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms (Advances in Systems Analysis, Software Engineering, and High Performance Computing)

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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms (Advances in Systems Analysis, Software Engineering, and High Performance Computing)

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms (Advances in Systems Analysis, Software Engineering, and High Performance Computing)

Category

Machine Learning

Author

Veljko Milutinovic

Nenad Mitic

Aleksandar Kartelj

Publication

Engineering Science Reference

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Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

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ISBN-10

1799883507

ISBN-13

978-1799883500

Publisher

Engineering Science Reference

Price

245

File Type

PDF

Page No.

296

Veljko Milutinovic

Veljko Milutinovic

Nenad Mitic

Aleksandar Kartelj

Aleksandar Kartelj

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