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
Assign5: CSCI4390-6390 Assign5 (Due: Nov 18th, Midnight)
Assign4: CSCI4390-6390 Assign4 (Due: Oct 29th, Midnight)
Assign3: CSCI4390-6390 Assign3 (Due: Oct 15th, Midnight)
Assign2: CSCI4390-6390 Assign2 (Due: Sep 24th, Midnight)
Assign1: CSCI4390-6390 Assign1 (Due: Sep 14th, Midnight)
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) | lecture2 |
| Sep 03 | Numeric Attributes II (Chapter 2) | lecture3 |
| Sep 07 | NO CLASS (Labor Day) | |
| Sep 10 | PCA (Chapter 7) | lecture4 |
| Sep 14 | PCA II and LDA I (Chapters 7 and 20) | lecture5 |
| Sep 17 | LDA II (Chap 20) | lecture6 |
| Sep 21 | Linear Regression I (Chapter 23) | lecture7 |
| Sep 24 | Linear Regression II (Chapter 23) | lecture8 |
| Sep 28 | EXAM I | |
| Oct 01 | Pattern Mining I (Chapter 8) | lecture9 |
| Oct 05 | Pattern Mining II (Chapter 9) | lecture10 |
| Oct 08 | Representative-Based Clustering I (Chapter 13) | lecture11 |
| Oct 12 | NO CLASS (Columbus Day) | |
| Oct 15 | Representative-Based Clustering II (Chapter 13) | lecture12 |
| Oct 16(F) | Density-based Clustering I (Chapter 15) | lecture13 |
| Oct 19 | Density-based Clustering II (Chapter 15) | lecture14 |
| Oct 22 | Spectral Clustering (Chapter 16) | lecture15 |
| Oct 26 | Clustering Validation (Chapter 17) | lecture16 |
| Oct 29 | Bayes Classifier (Chapter 18) | lecture17 |
| Nov 02 | EXAM II | |
| Nov 05 | Decision Trees (Chapter 19) | Decision Trees (A. Panda) |
| Nov 09 | Logistic Regression (Chapter 24) | lecture18 |
| Nov 12 | Support Vector Machines I (Chapter 21) | lecture19 |
| Nov 16 | SVMs II (Chapter 21) | |
| Nov 19 | Neural Networks I (Chapter 25) | |
| Nov 23 | NO CLASS (Thanksgiving) | |
| Nov 26 | NO CLASS (Thanksgiving) | |
| Nov 30 | Neural Networks II (Chapter 25) | |
| Dec 03 | Hopfield Networks | |
| Dec 07 | Wrapup | |
| Dec 10 | EXAM III |