CSCI4390-6390 Data Mining
This course focuses on fundamental algorithms and core concepts in data mining and machine learning. The emphasis is on leveraging geometric, algebraic and probabilistic viewpoints, as well as algorithmic implementation.
Class Hours: Troy 2012, 10AM-11:50AM Mon/Thurs
Instructor Office Hours: 12-1PM Mon/Thurs (MRC335)
TAs (Office Hours): Anweshit Panda (pandaa2@rpi.edu); Hours 2-3PM Tue/Wed (AE111)
Syllabus: CSCI4390-6390 Syllabus
Submitty: https://submitty.cs.rpi.edu/courses/f26/csci4390
Assignments
Class Schedule: Lectures
Tentative course schedule is given below. Lecture notes (in PDF) appear below.
| Date | Topic | Lectures |
|---|---|---|
| Aug 27 | Data Matrix/Numeric Attributes (Chapters 1&2) | lecture1 |
| Aug 31 | Numeric Attributes (Chapter 2) | |
| Sep 03 | Numeric Attributes (Chap 2) & High-dim Data (Chap 6) | |
| Sep 07 | NO CLASS (Labor Day) | |
| Sep 10 | High-dim Data (Chapter 6) | |
| Sep 14 | PCA (Chapter 7) | |
| Sep 17 | PCA II (Chapter 7) | |
| Sep 21 | Pattern Mining I (Chapter 8) | |
| Sep 24 | Pattern Mining II (Chapter 9) | |
| Sep 28 | EXAM I | |
| Oct 01 | Representative-Based Clustering I (Chapter 13) | |
| Oct 05 | Representative-Based Clustering II (Chapter 13) | |
| Oct 08 | Density-based Clustering (Chapter 15) | |
| Oct 12 | NO CLASS (Columbus Day) | |
| Oct 16(F) | Bayes Classifier (Chapters 18) | |
| Oct 19 | Decision Trees (Chapter 19) | |
| Oct 22 | Support Vector Machines I (Chapter 21) | |
| Oct 26 | Support Vector Machines II (Chapter 21) | |
| Oct 29 | Linear Regression (Chapter 23) | |
| Nov 02 | EXAM II | |
| Nov 05 | Linear Regression II (Chapter 23) | |
| Nov 09 | Logistic Regression (Chapter 24) | |
| Nov 12 | Neural Networks I (Chapter 25) | |
| Nov 16 | Neural Networks II (Chapter 25) | |
| Nov 19 | Modern Hopfield Networks I | |
| Nov 23 | NO CLASS (Thanksgiving) | |
| Nov 26 | NO CLASS (Thanksgiving) | |
| Nov 30 | Modern Hopfield Networks II | |
| Dec 03 | Assessment I (Chapters 17&22) | |
| Dec 07 | Assessment II (Chapters 17&22) | |
| Dec 10 | EXAM III |