CS 5973: Knowledge Discovery (and Data Mining)

The following is a preliminary schedule for CS 5973 Knowledge Discovery and Data Mining. This schedule will be updated as the semester progresses. Also, although it is not listed on each day, there will be project discussions every class period.

Date Topic Assigned Reading Assigned Due
Jan 16 (Week 1: Introduction)
No class, please read Barn-Raising paper
Jan 18 What is data mining? Seminar style classes, project discussions     Barn-Raising paper
Jan 23 (Week 2: Fundamentals) Introduction Chapter 1   Summary 1
Jan 25 Measurement and Data Chapter 2   Summary 2
Jan 30 (Week 3: Fundamentals)        
Feb 1 Visualizing and Exploring Data Chapter 3   Summary 3
Feb 6 (Week 4: Fundamentals)        
Feb 8 Data Analysis and Uncertainity Chapter 4   Summary 4
Feb 13 (Week 5: Fundamentals)     HW 1  
Feb 15 A Systematic Overview of Data Mining Algorithms Chapter 5   Summary 5, Project status 2
Feb 20 (Week 6: Building the toolbox) Score Functions for Data Mining Algorithms Chapter 7   Summary 6
Feb 22 Search and Optimization Methods Chapter 8   Summary 7, HW 1
Feb 27 (Week 7: Building the toolbox)       Status report 3
Mar 1 Descriptive Modeling Chapter 9   Summary 8
Mar 6 (Week 8: Building the toolbox)       Status report 4
Mar 8 Predictive Modeling Chapter 10   Summary 9
Mar 13 (Week 9: Building the toolbox)       Status report 5
Mar 15 Finding Patterns and Rules Chapter 13   Summary 10
Mar 17-25
Spring Break!
Mar 27 (Week 10: Applications) Getting 0.91 using SVD Simon's writeup HW 2 Summary 11
Mar 29 Learning from other netflix competitors Netflix forum analysis (see Jason's email)    
Apr 3 (Week 11: Applications) Semi-Supervised Time Series Classification Paper   Summary 12
Apr 5 Rule Interestingness Analysis Using OLAP Operations Paper   HW 2
Apr 10 (Week 12: Applications) What the prize administrators think we should do and discords Hinton paper AND Keogh paper   Summary 13
Apr 12 Dynamic Time Warping Paper    
Apr 17 (Week 13: Applications) Dynamic time warping II Paper   Summary 14
Apr 19 SVDs for rating systems Paper    
Apr 24 (Week 14: Applications) Collaborative Filtering via Gaussian Probabilistic Latent Semantic Analysis Paper   Lit review, Summary 15
Apr 26 Support Vector Machines Paper (first 3 sections)    
May 1 (Week 15: Applications) Project wrapup      
May 3 (Course wrapup) Project wrapup      
May 7
Final exam 4:30-6:30