Techniques of Artificial Intelligence by Vrije Universiteit Brussel
This note explains the following topics: State Space Search, Decision Trees, Evaluating Hypotheses, Evaluation of hypothesis, Neural Networks, Computational Learning Theory, DMF Clustering, Data Mining, Text Mining, Graph Mining, Text Mining.
Author(s): Vrije Universiteit Brussel
NA Pages 
Lecture note on Artificial Intelligence
This note describes the following topics: introduction to AI and production systems, Representation of Knowledge, Knowledge Representation using predicate logic, Knowledge Inference, Planning and Machine Learning, Expert Systems and Meta Knowledge.
Author(s): St Anne College of Engineering and Technology
173 Pages
Digital notes on Artificial Intelligence
This lecture note covers topics starting with an introduction to AI and progressing through various search strategies and A* search. The text delves into challenges such as searching with partial observations and constraint satisfaction problems, introducing techniques like Alpha Beta Pruning. It explores reasoning methods like forward and backward chaining, syntax and semantics of First-Order Logic, knowledge engineering, resolution, classical planning, and planning with state space search.it also handles with topics like acting in nondeterministic domains and multi-agent planning, Bayes Rule, Bayesian Networks and Dempster Shafer Theory.It includes learning decision trees and the role of knowledge in learning.
Author(s): Department of Information Technology , Malla Reddy College Of Engineering and Technology
143 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
Lecture Notes On Artificial Intelligence By Dr. Prashanta Kumar Patra
This book covers the following topics: AI Technique, Level of the Model,Problem Spaces, and Search: Defining the Problem as a State Space Search, Production Systems, Problem Characteristics, Production System Characteristics, Issues in the Design of Search Programs. Heuristic Search Techniques: Generate-andTest, Hill Climbing, Best-first Search, Problem Reduction, Constraint Satisfaction, Means-ends, Symbolic Reasoning Under Uncertainty, Game Playing, Learning: Rote Learning.
Author(s): Dr. Prashanta Kumar Patra
128 Pages
Machine Learning Advanced Techniques and Emerging Applications
This book covers recent advances of machine learning techniques in a broad range of applications in smart cities, automated industry, and emerging businesses.
Author(s): Hamed Farhadi
NA 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
