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Artificial Intelligence: A Modern Approach, 4e
Publisher:
Pearson Education
| Author:
Russell/Norvig
| Language:
english
| Format:
Paperback
₹718
Save: 30%
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ISBN:
Page Extent:
1292
The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.
Features
Nontechnical learning material introduces major concepts using intuitive explanations, before going into mathematical or algorithmic details.
A unified approach to AI shows students how the various subfields of AI fit together to build actual, useful programs.
In-depth coverage of both basic and advanced topics provides students with a basic understanding of the frontiers of AI without compromising complexity and depth.
NEW – New chapters feature expanded coverage of probabilistic programming; multiagent decision making; deep learning; and deep learning for natural language processing.
Description
The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.
Features
Nontechnical learning material introduces major concepts using intuitive explanations, before going into mathematical or algorithmic details.
A unified approach to AI shows students how the various subfields of AI fit together to build actual, useful programs.
In-depth coverage of both basic and advanced topics provides students with a basic understanding of the frontiers of AI without compromising complexity and depth.
NEW – New chapters feature expanded coverage of probabilistic programming; multiagent decision making; deep learning; and deep learning for natural language processing.
About Author
Stuart Russell has received his B.A. with firstclass honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor and former chair of computer science, director of the Center for Human-Compatible AI, and holder of the Smith?Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was cowinner of the Computers and Thought Award. Peter Norvig is currently a Director of Research at Google, Inc., and was previously the director responsible for the core Web search algorithms. He co-taught an online AI class that signed up 160,000 students, helping to kick off the current round of massive open online classes. He received a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from Berkeley. He has been a professor at the University of Southern California and a faculty member at Berkeley and Stanford. The two authors shared the inaugural AAAI/EAAI Outstanding Educator award in 2016.
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