Share
Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Veljko Milutinovic
(Author)
·
Nenad Mitic
(Author)
·
Aleksandar Kartelj
(Author)
·
Engineering Science Reference
· Paperback
Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms - Milutinovic, Veljko ; Mitic, Nenad ; Kartelj, Aleksandar
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My Wishlists
Origin: U.S.A.
(Import costs included in the price)
It will be shipped from our warehouse between
Wednesday, July 24 and
Wednesday, July 31.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.
Synopsis "Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms"
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.
