Class Schedule

CS 249: Special Topics - Advanced Data Mining

News

[04/10/2017] Book refers to: Jiawei Han, Micheline Kamber, and Jian Pei, Data Mining: Concepts and Techniques, 3rd edition.

[04/03/2017] First day of classes. The instructor will be traveling in the first week, guest lectures will be delivered by Ting Chen and Yupeng Gu.

Class Schedule

(Future lectures and events are tentative.)

Week#	Date	Topic	Further Reading	Homework	Course Project
1	Apr. 3	Introduction [slides]	Book Chapter 1, 2, 3
1	Apr. 5	Math Review: linear algebra, probability and statistics, optimization [slides]	Review of probability from a course by David Bleifrom Princeton U. Machine Learning Math Essentials by Jeff Howbert from Washington U. http://cs229.stanford.edu/section/cs229-prob.pdf
2	Apr. 10	Linear Regression; Logistic Regression; Generalized Linear Model [slides]	http://cs229.stanford.edu/notes/cs229-notes1.pdf
2	Apr. 12	Decision Tree; Regression Tree; Random Forest [slides]	Decision Tree: Book Chapter 8.1, 8.2 Regression Tree: http://www.stat.cmu.edu/~cshalizi/350-2006/lecture-10.pdf Random Forest: https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm	HW1 out	Group formation due
3	Apr. 17	MLE and Naïve Bayes [slides]	Notes on derivation of P(C_j) in Naive Bayes
3	Apr. 19	SVM; Neural Network [slides]	Notes on SVM by Andrew Ng: http://cs229.stanford.edu/notes/cs229-notes3.pdf http://neuralnetworksanddeeplearning.com/ http://www.deeplearningbook.org/	HW1 due
4	Apr. 24	Classification Evaluation; Other Practical Issues [slides]	Book Chapter 8.5	HW2 out
4	Apr. 26	K-means; Hierarchical Clustering; DBSCAN [slides]	Book Chapter 10.1-10.4
5	May 1	Mixture Models; Kernel K-means [slides]	Notes on mixture models and EM algorithm: http://www.stat.cmu.edu/~cshalizi/350/lectures/29/lecture-29.pdf http://www.cs.ubc.ca/~murphyk/Teaching/CS340-Fall06/reading/mixtureModels.pdf
5	May 3	Clustering Evaluation; Other Practical Issues [slides]	Book Chapter 10.6, 2.4	HW2 due HW3 out
6	May 8	Topic Models [slides]			Proposal due
6	May 10	Word Embedding [slides]		HW3 due
7	May 15	Midterm Exam
7	May 17	Recommender Systems I [slides]
8	May 22	Recommender Systems II [slides]
8	May 24	Recommender Systems II (continue from last class)
9	May 29	No Class (Memorial Day)
9	May 31	Information Network Mining [slides]
10	Jun. 5	Project Presentation
10	Jun. 7	Project Presentation
11	Jun. 12	No Class			Report due