Stock photo: cover may vary
Algorithms in Machine Learning Paradigms (Studies in Computational Intelligence) Hardback - 2020
by Mandal, Jyotsna Kumar (Editor) / Mukhopadhyay, Somnath (Editor) / Dutta, Paramartha (Editor) / Dasgupta, Kousik (Editor)
- New
- Hardback
A$449.32
A$29.29
Delivery to USA
Standard delivery: 7 to 14 days
More delivery options
Standard delivery: 7 to 14 days
Ships from Revaluation Books (Devon, United Kingdom)
Details
- Title Algorithms in Machine Learning Paradigms (Studies in Computational Intelligence)
- Author Mandal, Jyotsna Kumar (Editor) / Mukhopadhyay, Somnath (Editor) / Dutta, Paramartha (Editor) / Dasgupta, Kousik (Editor)
- Binding Hardback
- Condition New
- Pages 195
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2020
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # x-9811510407
- ISBN 9789811510403 / 9811510407
- Weight 1.03 lbs (0.47 kg)
- Dimensions 9.21 x 6.14 x 0.5 in (23.39 x 15.60 x 1.27 cm)
- Category Mathematics
- Dewey Decimal Code 006.31
- Quantity available 2
About Revaluation Books Devon, United Kingdom
Biblio member since 2020
General bookseller of both fiction and non-fiction.
Reader reviews for Algorithms in Machine Learning Paradigms (Studies in Computational Intelligence)
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the rear cover
This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.
