Schedule for CSCE 41403, Section 1: Data Mining
(This will be changed frequently. Please check this page before class every week.)
Date | Topics Covered | Reading Assignment(before class) | Handout |
Aug 19 | Class overview | Chapter 1 | DS overview |
Aug 21 | Data mining programming | Machine learning in Python | |
Aug 26 | Classification | Chapter 8 (skip 8.4) | ch8
entropy (optional) |
Sept 2 | |||
Sept 4 | |||
Sept 9 | Logistic regression | Logistic regression | Logistic regression |
Sept 11 | |||
Sept 16 | Introduction to foundation models |
|
guest lecture on VLMs |
Sept 18 | Project implementation | ||
Sept 23 | Mining frequent patterns, associations and correlations | Chapter 6 (skip 6.2.3-6.2.6) | ch6 |
Sept 25 | |||
Sept 30 | Cluster analysis | Chapter 10 | kNN |
Oct 2 | |||
Oct 7 | Classification: Advanced methods | Chapter 9 | ch9 |
Oct 9 | Midterm | ||
Oct 14 | Fall break | ||
Oct 16 | SVM | SVM-reading | SVM |
Oct 21 | |||
Oct 23 | Graph Mining | Link analysis | Social network analysis |
Oct 28 | |||
Oct 30 | |||
N0v 4 | |||
Nov 6 | Dimension Reduction | Chapter 3 | ch3 |
Nov 11 | Causal modeling and inference | Judea Pearl’s tutorials | Dr. Lu Zhang’s guest lecture slides |
Nov 13 | Project presentation | 7 minute (including 1-minute Q/A) for each presentation | |
Nov 18 | Project presentation | 7 minute (including 1-minute Q/A) for each presentation | |
Nov 20 | Project presentation | 7 minute (including 1-minute Q/A) for each presentation | |
Nov 25 | Privacy preserving data mining | Differential Privacy | Privacy preserving data mining |
Dec 2 | Big Data Analytics | MapReduce | MapReduce |
Dec 4 | Deep learning models | Tutorial 1 and 2 | DL Introduction |
Dec 9 (10:15am-12:15pm) | Final exam |