Lectures

games || || Tim Jones - Chapter 4 || Alpha-beta pruning ||  ||   || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 || Naive Bayes Classification, || ||   || Weka: []
 * **Lecture #** || Date || **Topic** || **Lecture** || **Reading Material** ||
 * 1 || 4th Feb || Course Overview, AI - Introduction, History || [[file:Introduction to AI Unit 1.pdf]] || Tim Jones - Chapter 1 ||
 * 2 || 8th Feb || Problem solving as search, Search Space, DFS, BFS || [[file:Introduction to AI Unit 2.pdf]] || Tim Jones - Chapter 2 ||
 * 3 || 11th Feb || DFS, BFS, Iterative Deepening Search, Informed Searches || [[file:Introduction to AI Unit 3.pdf]] || Tim Jones - Chapter 2 ||
 * 4 || 15th Feb || Best-first search, A* Search || [[file:Introduction to AI Unit 4.pdf]] || Tim Jones - Chapter 3 ||
 * 5 || 18th Feb || Greedy Search, Hill Climbing, Global vs loval mimima, Search in adversarial
 * 6 || 23rd Feb || Minimax Algorithm,
 * 7 || 25th Feb || Quiz, Alpha-beta pruning, Machine Learning Intro ||  || Tim Jones - Chapter 6
 * 8 || 29th Feb || Decision Trees, GINI Index || [[file:Introduction to AI Unit 8-9-10.pdf]] || im Jones - Chapter 6
 * 9 || 3rd Mar || Decision Tree Induction, Entropy, Classification Accuracy ||  || Tim Jones - Chapter 6
 * 10 || 7th Mar || Naive Bayes Classification ||  || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 ||
 * ||  || Term Exam - 1 ||   ||   ||
 * 11 || 21st Mar || Review of Exam copies,
 * 12 || 24th Mar || Neural Networks || [[file:Introduction to AI - ANN.pdf]] ||  ||
 * 13 || 28th Mar || Neural Networks ||  ||   ||
 * 14 || 7th Apr || Clustering, k-means || [[file:Introduction to AI Unit - KMeans.pdf]] ||  ||
 * 15 || 8th Apr || K-means algorithm ||  ||   ||
 * 16 || 8th Apr || Weka, KNIME, ||  || Download links:

KNIME: [] || []
 * 17 || 11th Apr || Logic and Reasoning - Propositional & Predicate logic || [[file:Introduction to AI - Logic and Reasoning.pdf]] || SWI-Prolog Download:

Prolog Samples: http://www.csse.monash.edu.au/~lloyd/tildeLogic/Prolog.toy/Examples/ || Probabilistic Reasoning || ||   || Serial, Converging, and Diverging Connections, ||  ||   ||
 * 18 || 14th Apr || Prolog Samples,
 * 19 || 18th Apr || Revision, Project Discussions ||  ||   ||
 * ||  || TERM EXAM - II ||   ||   ||
 * 20 || 28th Apr || Bayesian Networks ||  ||   ||
 * 21 || 2nd Apr || Inference in Bayesian network ||  ||   ||
 * 22 || 5th Apr || d-seperation, Markov Blanket
 * 23 || 9th Apr || GeNie, Term Exam-II result ||  || http://genie.sis.pitt.edu/downloads.html ||
 * 24 ||  || Evolutionary Algorithms || [[file:Introduction to AI Unit 12 - Evolutionary Algorithms.pdf]] ||   ||   ||
 * 25 ||  || Evolutionary Algorithms ||   ||   ||
 * 26 ||  || Swarm Intelligence ||   ||   ||
 * 27 ||  || Swarm Intelligence || [[file:Introduction to AI Unit-Swarm Intelligence.pdf]] ||   ||
 * 28 ||  || Kinect ||   ||   ||
 * 29-30 ||  || Project Demos ||   ||   ||