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Introduction to Artificial Intelligence Lecture Notes
This book explains the following topics: Principles of knowledge-based search techniques, automatic deduction, knowledge representation using predicate logic, machine learning, probabilistic reasoning, Applications in tasks such as problem solving, data mining, game playing, natural language understanding, computer vision, speech recognition, and robotics.
Author(s): Chuck Dyer
NA Pages 
Explorations in Artificial Intelligence and Machine Learning
This PDF covers the following topics related to Artificial Intelligence and Machine Learning : Introduction to Machine Learning,The Bayesian Approach to Machine Learning, A Revealing Introduction to Hidden Markov Models, Introduction to Reinforcement Learning, Deep Learning for Feature Representation, Neural Networks and Deep Learning, AI-Completeness: The Problem Domain of Super-intelligent Machines.
Author(s): Prof. Roberto V. Zicari
178 Pages
Introduction to Artificial Intelligence by Bojana Dalbelo Basic and Jan Snajder
This note covers the following topics: Atlas: humanoid robot, VoiceTra Real-Time Machine Translation, DeepMind&
Author(s): Prof. Bojana Dalbelo Basic and Assoc. Prof. Jan Snajder
79 Pages
Introduction to Artificial Intelligence Lecture Notes
This book explains the following topics: Principles of knowledge-based search techniques, automatic deduction, knowledge representation using predicate logic, machine learning, probabilistic reasoning, Applications in tasks such as problem solving, data mining, game playing, natural language understanding, computer vision, speech recognition, and robotics.
Author(s): Chuck Dyer
NA Pages
Artificial Intelligence Lecture Materials
This note will provide an introduction to the field of Artificial Intelligence. It will cover a number of AI ideas and techniques, as well as give you a brief introduction to symbolic computing.
Author(s): Diane Cook
NA Pages
Introduction to Artificial Intelligence
This note explains the following topics: Search, Game playing, Logic, Planning, Probabilistic reasoning, Decision theory, Markov decision processes, POMDPs, Game theory, Machine learning, Wrapping up.
Author(s): Vincent Conitzer
NA Pages
Artificial Intelligence by Professor Yun Peng
This note is designed as a broad rather than in-depth introduction to the principles of artificial intelligence, its characteristics, major techniques, and important sub-fields and applications.
Author(s): Professor Yun Peng
NA Pages
Artificial Intelligence Course Notes
This note explains artificial intelligence, including agent design, heuristic search, knowledge representation, planning, logic, natural language processing and machine learning.
Author(s): Ray Toal
NA Pages
Building Expert Systems In Prolog (Amzi)
Currently this section contains no detailed description for the page, will update this page soon.
Author(s):
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Introduction to Machine Learning (N. Nilsson)
This note covers the following topics: Preliminaries, Boolean Functions, Using Version Spaces for Learning, Statistical Learning, Decision Trees, Inductive Logic Programming , Computational Learning Theory, Unsupervised Learning, Temporal-Difference Learning, Delayed-Reinforcement Learning.
Author(s): Nils J. Nilsson
NA Pages
Introduction to Machine Learning
Currently this section contains no detailed description for the page, will update this page soon.
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