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Item Details
Title:
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MACHINE LEARNING
PARADIGMS AND METHODS |
By: |
Jaime G. Carbonell (Editor) |
Format: |
Paperback |
List price:
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£38.00 |
We currently do not stock this item, please contact the publisher directly for
further information.
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ISBN 10: |
0262530880 |
ISBN 13: |
9780262530880 |
Publisher: |
MIT PRESS LTD |
Pub. date: |
23 February, 1990 |
Series: |
Special Issues of Artificial Intelligence |
Pages: |
400 |
Description: |
Having played a central role at the inception of artificial intelligence research, machine learning has recently reemerged as a major area of study at the very core of the subject. |
Synopsis: |
Having played a central role at the inception of artificial intelligence research, machine learning has recently reemerged as a major area of study at the very core of the subject. Solid theoretical foundations are being constructed. Machine learning methods are being integrated with powerful performance systems, and practical applications; based on established techniques are emerging.Machine Learning unifies the field by bringing together and clearly explaining the major successful paradigms for machine learning: inductive approaches, explanation-based learning, genetic algorithms, and connectionist learning methods. Each paradigm is presented in depth, providing historical perspective but focusing on current research and potential applications.The contributors are: John R. Anderson, L. B. Booker, John. H. Gennari, Jaime G. Carbonell, Oren Etzioni, Doug Fisher, Yolanda Gil, D. E. Goldberg, Gerald E. Hinton, J. H. Holland, Craig A Knoblock, Daniel. R. Kuokka, Pat Langley, David B. Leake, Steve Minton, Jack Mostow, Roger C. Schank, and Jan M. Zytkow.Jaime G. Carbonell is Professor of Computer Science at Carnegie-Mellon University. |
Publication: |
US |
Imprint: |
MIT Press |
Returns: |
Returnable |
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Ramadan and Eid al-Fitr
A celebratory, inclusive and educational exploration of Ramadan and Eid al-Fitr for both children that celebrate and children who want to understand and appreciate their peers who do.
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