Class Schedule

CS 145: Introduction to Data Mining

News

[10/24/2018] Schedule has been updated.

[10/1/2018] First day of class.

[10/1/2018] Book refers to: Jiawei Han, Micheline Kamber, and Jian Pei, Data Mining: Concepts and Techniques, 3rd edition.

 


Class Schedule

(Future lectures and events are tentative.)

Week#

Date

Topic

Further Reading

Discussion Session

Homework

Course Project

1

Oct. 1

Introduction [slides] and Math Review

 

 

 

1

Oct. 3

Linear Regression [slides];

 

 

2

Oct. 8

Logistic Regression [slides];

Course Project Introduction [slides]

 

 

 

 

2

Oct. 10

Decision Tree; Regression Tree; Random Forest [slides]

 

HW1 out

Group formation due

3

Oct. 15

SVM [slides]

 

 

 

 

3

Oct. 17

SVM (continue)

 

HW1 due

 

 

4

Oct. 22

Neural Network [slides]

 

HW2 out

 

4

Oct. 24

Neural Network (continue)

 

 

 

 

5

Oct. 29

Similarity measure and KNN [slides]

Classification Evaluation; Other Practical Issues [slides]


  • Book Chapter 8.5
   

HW2 due

 

 

5

Oct. 31

Clustering Basics: K-means; Hierarchical Clustering; DBSCAN [slides]

  • Book Chapter 10.1-10.4

HW3 out

 

 

6

Nov. 5

Mixture Models [slides]

 

 

 

6

Nov. 7

Clustering Evaluation; Other Practical Issues [slides]

  • Book Chapter 10.6, 2.4

HW3 due

HW4 out

 

7

Nov. 12

Veterans Day Holiday (no class)

 

 

Midterm Report due

7

Nov. 14

Midterm Exam (in-class)

 

 
  • Midterm Paper Review

 

 

8

Nov. 19

Frequent Pattern Mining and Association Rules I [slides]

.
  • Book Chapter 6
 

HW4 due

 

8

Nov. 21

Frequent Pattern Mining and Association Rules II

  • Book Chapter 6
 
  • Thanksgiving Holiday

 HW5 out

 

9

Nov. 26

Sequential Pattern Mining [slides]; DTW [slides]

 

 

 

9

Nov. 28

Naive Bayes for Text [slides]

HW5 due

HW6 out (Optional)

 

10

Dec. 3

Topic Model [slides]

 

 

 

10

Dec. 5

Final review [slides]

 

  • Go over course material

 HW6 due (Optional)

Final Report due (Dec. 11th)

11

Dec. 13

Final Exam (11:30am-2:30pm)