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First publish date: 1978
Authors: Richard Ernest Bellman
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An introduction to artificial intelligence by Richard Ernest Bellman

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Books similar to An introduction to artificial intelligence (8 similar books)

The Elements of Statistical Learning by 12158869|Trevor Hastie book cover

📘 The Elements of Statistical Learning
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The Elements of Statistical Learning explains key statistical methods that underlie modern machine learning, data mining, and bioinformatics, covering supervised and unsupervised learning techniques such as classification trees, neural networks, and support vector machines.

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Deep Learning by 11775475|Ian Goodfellow book cover

📘 Deep Learning
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Deep Learning is a comprehensive textbook that equips students and practitioners with the foundational knowledge and practical skills needed to enter the fields of machine learning and deep learning.

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Introduction to Machine Learning with Python by 11655721|Andreas C. Mueller book cover

📘 Introduction to Machine Learning with Python
 by Andreas C. Mueller


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Introducing Artifical Intelligence by 7443988|Henry Brighton book cover

📘 Introducing Artifical Intelligence
 by Henry Brighton


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Introduction to Machine Learning by 4295122|Ethem Alpaydin book cover

📘 Introduction to Machine Learning
 by Ethem Alpaydin


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Pattern Recognition and Machine Learning by 8824929|Christopher M. Bishop book cover

📘 Pattern Recognition and Machine Learning
 by Christopher M. Bishop


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An introduction to artificial intelligence by 6946517|Janet Finlay book cover

📘 An introduction to artificial intelligence
 by Janet Finlay

"In this authoritative and accessible one-stop introduction to artificial intelligence, a full first course in AI is presented, making it ideal for a modular undergraduate degree scheme or Masters conversion course." "The book has been designed to provide an understanding of the foundations of artificial intelligence. It examines the central computational techniques embraced by AI - knowledge representation, search, reasoning and learning - and the principal application domains - experts systems, natural language, vision, robotics, software agents and cognitive modelling. In a concluding section some of the major philosophical and ethical issues of AI are also introduced."--BOOK JACKET.

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Bayesian reasoning and machine learning by 11367792|David Barber book cover

📘 Bayesian reasoning and machine learning
 by David Barber

A practical guide to Bayesian methods in machine learning, tailored for undergraduates and graduate students with modest math backgrounds.

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Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
Machine Learning: A Probabilistic Perspective by Kevin P. Murphy
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Artificial Intelligence: Foundations of Computational Agents by David L. Poole and Alan K. Mackworth
Learning from Data by Yann LeCun, Léon Bottou, Graham B. Orr, and Klaus-Robert Müller
Probabilistic Graphical Models: Principles and Techniques by Daphne Koller and Nir Friedman
Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
Machine Learning: A Probabilistic Perspective by Kevin P. Murphy
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Artificial Intelligence: Foundations of Computational Agents by David L. Poole and Alan K. Mackworth
Probabilistic Graphical Models: Principles and Techniques by Daphne Koller and Nir Friedman

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