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Digital Notes on Artificial Intelligence by Sri Indu College of Engineering and Technology
This note explains the following topics: Problem Solving by Search , Knowledge and Reasoning, Planning Classical Planning, Uncertain knowledge and Learning.
Author(s): Department of CSE, Sri Indu College of Engineering and Technology
140 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
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
Artificial Intelligence Lecture Notes Veer Surendra Sai University
This lecture note covers the following topics: Formalized symbolic logic, Probabilistic Reasoning Structured knowledge, graphs, frames and related structures, Matching Techniques, Knowledge organizations, Management, Natural Language processing, Pattern recognition, expert systems.
Author(s): Prof. Pradipta Kumar Das, Prof. D. Chandrasekhar Rao and Prof. Kishore Kumar Sahu
213 Pages
Techniques in Artificial Intelligence
This note provides an introduction to artificial intelligence. Topics covered include: representation and inference in first-order logic, modern deterministic and decision-theoretic planning techniques, basic supervised learning methods, and Bayesian network inference and learning.
Author(s): Prof. Tomas Lozano-Perez and Prof. Leslie Kaelbling
NA Pages
Artificial Intelligence Lecture Notes
This course note covers major topics of AI, including Search, Logic and Knowledge Representation, and Natural Language Processing, with brief coverage of the Brain and Machine Vision.
Author(s): Gordon S. Novak Jr
NA Pages
Artificial Intelligence Lectures slides and readings
This note covers the following topics: Search, Backtracking Search, Game Tree Search, Reasoning Under Uncertainty, Planning, Decision Making under Uncertainty.
Author(s): Fahiem Bacchus
NA Pages
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
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Author(s):
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