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Books like Artificial intelligence today by Michael J. Wooldridge


First publish date: 1999
Authors: Michael J. Wooldridge
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Artificial intelligence today by Michael J. Wooldridge

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Books similar to Artificial intelligence today (8 similar books)

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📘 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
 by Ian Goodfellow

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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Natural Language Processing With Python by 11141535|Edward Loper book cover

📘 Natural Language Processing With Python
 by Edward Loper

An accessible guide to Natural Language Processing, teaching Python programming for text analysis and language technology applications such as predictive text, email filtering, summarization, and translation.

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Empirical methods for artificial intelligence by 10208465|Paul R. Cohen book cover

📘 Empirical methods for artificial intelligence
 by Paul R. Cohen


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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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Introduction to artificial intelligence by 2572411|Philip C. Jackson book cover

📘 Introduction to artificial intelligence
 by Philip C. Jackson


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Knowledge representation by 13179228|Han Reichgelt book cover

📘 Knowledge representation
 by Han Reichgelt


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Artifical intelligence by 861382|Fred D'Ignazio book cover

📘 Artifical intelligence
 by Fred D'Ignazio


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Some Other Similar Books

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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