machine learning Books
We've found 24 books tagged 'machine learning' relevant to the field of humanlike conversational artificial intelligence.
| Publisher: |
Springer
|
| Year: |
1999 |
| Order: |
http://www.amazon.com/Conversa... |
Summary: Machine Conversationsis a collection of some of the best research available in the practical arts of machine conversation. The book describes various attempts to create practical and flexible machine conversation - ways of talking to computers in an unrestricted version of English or some other...
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11217
by Jan van Kuppevelt, Laila Dybkjær and Niels Ole Bernsen |
| Publisher: |
Springer
|
| Year: |
2006 |
| Order: |
http://www.amazon.com/Advances... |
Summary: The main topic of this volume is natural multimodal interaction. The book is unique in that it brings together a great many contributions regarding aspects of natural and multimodal interaction written by many of the important actors in the field. Topics addressed include talking heads,...
| Subtitle: |
Introduction to |
| Publisher: |
The MIT Press
|
| Year: |
2009 |
| Order: |
http://www.amazon.com/Introduc... |
Summary: The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that...
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10447
by Tom Michael Mitchell |
Summary: This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
| Subtitle: |
and Scientific Method |
| Publisher: |
Oxford University Press
|
| Year: |
1996 |
| Order: |
http://www.amazon.com/Artifici... |
Summary: Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies focuses on two key topics within AI: machine learning in the Turing...
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10439
by Jimmy Lin, Chris Dyer and Graeme Hirst |
Summary: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing...
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10432
by Christopher M. Bishop |
| Publisher: |
Springer
|
| Year: |
2007 |
| Order: |
http://www.amazon.com/Pattern-... |
Summary: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply...
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10431
by Ian H. Witten, Eibe Frank and Mark A. Hall |
| Subtitle: |
Practical Machine Learning Tools and Techniques |
| Publisher: |
Morgan Kaufmann
|
| Year: |
2011 |
| Order: |
http://www.amazon.com/Data-Min... |
Summary: Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data...
| Publisher: |
The MIT Press
|
| Year: |
1996 |
| Order: |
http://www.amazon.com/Statisti... |
Summary: Eugene Charniak breaks new ground in artificial intelligenceresearch by presenting statistical language processing from an artificial intelligence point of view in a text for researchers and scientists with a traditional computer science background.New, exacting empirical methods are needed to break the deadlock in such areas...
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10428
by Stephen Marsland |
| Subtitle: |
An Algorithmic Perspective |
| Publisher: |
CRC
|
| Year: |
2009 |
| Order: |
http://www.amazon.com/Machine-... |
Summary: Traditional books on machine learning can be divided into two groups — those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates...
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