CAP5771 Principles of Data Mining

Spring 2017

Course Calendar (tentative)

Class # Date Lecture Reading Assignments
Week 1
1 1/10 Introduction & Logistics Ch. 1 Group Members (Due 1/20), Project Proposal (Due 1/31)
2 1/12 Knowing Your Data Ch. 2.1-2.3
Week 2
3 1/17 Weka 1. Introduction to WEKA
2. Weka (Tutorial) (Data Processing with Weka)
3. Datasets in Weka Arff Formats
Bring your laptop to the class.
4 1/19 Weka Practice Bring your laptop to the class. Weka exercise (Due: 1/26)
Week 3
5 1/24 Knowing Your Data: Measuring Data Similarity Ch. 2.4
6 1/26 Data Exploration Ch. 3
Week 4
7 1/31 Classification: Decision Tree 4.1-4.3 Project on Classification (Due: 2/23)
8 2/2 Classification: Decision Tree Pruning 4.4-4.6
Week 5
9 2/7 Classification: Model Evaluation 5.2-5.4
10 2/9 Classification: KNN & Bayes 5.4
Week 6
11 2/14 No class. Instructor will be traveling.
12 2/16 Classification: SVM & Ensemble Methods 5.5-5.6
Week 7
13 2/21 Classification: Neural Network & Deep Learning
14 2/23 Association Analysis: Concepts 6.1-6.3 Project on Association (Due: 3/21)
Week 8
15 2/28 No class.
16 3/2 Association Analysis: Apriori 6.4-6.6
Week 9
17 3/7 Association Analysis: FP-Growth 6.7-6.8
18 3/9 Association Analysis: Interestingness Measure
Week 10
19 3/14 No Class in Spring Break Final Project (Due: 4/25)
20 3/16 No Class in Spring Break
Week 11
21 3/21 No class. Midterm Self-Review
22 3/23 Midterm Exam
Week 12
23 3/28 Midterm Question Review
24 3/30 Clustering: Introduction, Partitioning Methods 8.1-8.2 Project 3: Clustering (Optional) (Due: 4/13)
Week 13
25 4/4 Clustering: Hierarchical Methods (Student Presentation) 8.3-8.4
26 4/6 Deep Learning: Convolutional Neural Networks (Student Presentation)
Week 14
27 4/11 Deep Learning: Recurrent Neural Networks (Student Presentation)
28 4/13 Deep Learning: Tensorflow (Guest Lecture)
Week 15
29 4/18 No class. Work on the Final Project.
30 4/20 No class. Work on the Final Project.
Week 16
31 4/25 Final Project Presentation (6:25pm-10:00pm).