Lectures

Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 || Clustering ||  ||   ||
 * **Lecture #** || **Date** || **Topic** || **Lecture** || **Reading Material** ||
 * 1 || 15/02 || Course Overview, AI - Introduction, History || [[file:Introduction to AI Unit 1.pdf]] || Tim Jones - Chapter 1 ||
 * 2 || 18/02 || Problem solving as search, Search Space || [[file:Introduction to AI Unit 2.pdf]] || Tim Jones - Chapter 2 ||
 * 3 || 22/02 || Depth-first search, Breadth-first search, Best-first Search || [[file:Introduction to AI Unit 3.pdf]] || Tim Jones - Chapter 2 ||
 * 4 || 25/02 || Best-first search, A* Search, Greedy algorithm, Hill climbing || [[file:Introduction to AI Unit 4.pdf]] || Tim Jones - Chapter 3 ||
 * 5 || 01/03 || Search in adversarial games, Minimax Algorithm || [[file:Introduction to AI Unit 5.pdf]] || Tim Jones - Chapter 4 ||
 * 6 || 08/03 || Alpha-beta pruning, OLTP vs OLAP vs Datamining ||  ||   ||
 * 7 || 11/03 || Machine Learning - Classification vs Clustering, Decision Trees || [[file:Introduction to AI Unit 6.pdf]] || Tim Jones - Chapter 6
 * 8 || 15/03 || Decision Trees, GINI Index, Entropy || [[file:Introduction to AI Unit 7.pdf]] || Tim Jones - Chapter 6
 * 9 || 15/03 || Decision Trees, GINI Index, Entropy ||  || Tim Jones - Chapter 6
 * 10 || 18/03 || Naive Bayes Classification ||  || Data Mining - Concepts & Techniques (Han, Kamber) - Chapter 6 ||
 * 11 || 22/03 || Naive Bayes Classification, Metrics for performance evaluation (Accuracy, Precision, Recall etc) ||  ||   ||
 * || 29/03 || Term Exam - 1 ||  ||   ||
 * 12 || 01/04 || Neural Networks ||  ||   ||
 * 13 || 05/04 || Neural Networks || [[file:Introduction to AI Unit 8.pdf]] ||  ||
 * || 08/04 || Out of Country ( IranOpen 2011) ||  ||   ||
 * || 12/04 || Out of Country ( IranOpen 2011) ||  ||   ||
 * 14 || 15/04 || Neural Networks ||  ||   ||
 * 15 || 19/04 || Review of Term Exam - I copies,
 * 16 || 22/04 || Clustering, k-means || [[file:Introduction to AI Unit 9.pdf]] ||  ||
 * 17 || 22/04 || K-means algorithm, Project discussions ||  ||   ||
 * 18 || 26/04 || Logic and Reasoning - Propositional & Predicate logic || [[file:Introduction+to+AI+Unit+10.pdf]] || http://www.csse.monash.edu.au/~lloyd/tildeLogic/Prolog.toy/Examples/ ||
 * 19 || 29/04 || Logic and Reasoning - Propositional & Predicate logic ||  ||   ||
 * 20 || 29/04 || Prolog, Bayesian Network ||  ||   ||
 * 21 || 03/05 || Bayesian Networks || [[file:Introduction to AI Unit 11.pdf]] ||  ||
 * 22 || 13/05 || Inference in Bayesian network ||  ||   ||
 * 23 || 17/05 || d-seperation, Markov Blanket, Serial, Converging, and Diverging connections ||  ||   ||
 * 24 || 20/05 || GeNie, IBAyes, Term Exam-II result ||  || http://genie.sis.pitt.edu/downloads.html ||
 * 25 || 24/05 || Evolutionary Algorithms || [[file:Introduction to AI Unit 12.pdf]] ||  ||   ||
 * 26 || 27/05 || Evolutionary Algorithms ||  ||   ||
 * 27,28 || 29/05 || Computer Vision - Guest Lecture by Mr. Ali Zaidi ||  ||   ||
 * 29 || 31/05 || Swarm Intelligence || [[file:Introduction to AI Unit 13.pdf]] ||  ||
 * 30 || 03/05 || Swarm Intelligence ||  ||   ||
 * 31 || 07/05 || Project Demos ||  ||   ||