Download the fantastic book titled Implementation of Machine Learning Algorithms Using Control Flow and Dataflow Paradigms written by Milutinovi?, Veljko, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Implementation of Machine Learning Algorithms Using Control Flow and Dataflow Paradigms", which was released on 11 March 2022. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.
Summary of Implementation of Machine Learning Algorithms Using Control Flow and Dataflow Paradigms by Milutinovi?, Veljko PDF
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.
Detail About Implementation of Machine Learning Algorithms Using Control Flow and Dataflow Paradigms PDF
- Author : Milutinovi?, Veljko
- Publisher : IGI Global
- Genre : Computers
- Total Pages : 296 pages
- ISBN : 1799883523
- Release Date : 11 March 2022
- PDF File Size : 43,9 Mb
- Language : English
- Rating : 5/5 from 1 reviews
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