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.
This class will be online for the entire semester, and live class videos will be using webex link below.
Webex Lectures: https://rensselaer.webex.com/meet/zakim
Class Hours: 10:10AM-12:00PM Tue/Fri Online via Webex
Instructor Office Hours: 12-1PM Tue/Fri
TA: Abhishek Gupta guptaa10@rpi.edu
TA Office Hours: 3-4PM Wed and 4-5PM on Thurs via Webex (https://rensselaer.webex.com/meet/guptaa10)
Syllabus: CSCI4390-6390 Syllabus
Campuswire: https://campuswire.com/c/GC1A29D57/
Submitty: https://submitty.cs.rpi.edu/courses/f20/csci4390
Assignments
Assign1: CSCI4390-6390 Assign1 (Due Date: Sep 11th)
Assign2: CSCI4390-6390 Assign2 (Due Date: Sep 22nd)
Class Schedule: Lectures
Tentative course schedule is given below. The topics are subject to change, but the dates for the Exams are fixed.
Date |
Topic |
Lecture Notes & Videos |
|---|---|---|
Sep 01 |
Introduction & Data Matrix (Chapter 1) |
|
Sep 04 |
Data Matrix/Numeric Attributes (Chapter 2) |
|
Sep 08 |
NO CLASS (Monday Schedule) |
|
Sep 11 |
Numeric Attributes (Chapter 2) |
|
Sep 15 |
Dimensionality Reduction (Chapter 7) |
|
Sep 18 |
High Dimensional Data (Chapter 6) |
|
Sep 22 |
High Dimensional Data II (Chap 6) & Kernel Methods (Chapter 5) |
|
Sep 25 |
EXAM I |
|
Sep 29 |
Kernel Methods II (Chapter 5) |
|
Oct 02 |
Linear Regression I (Chapter 23) |
|
Oct 06 |
Linear Regression II (Chapter 23) |
|
Oct 09 |
Logistic Regression (Chapter 24) |
|
Oct 13 |
Neural Networks I (Chapter 25) |
|
Oct 16 |
Neural Networks II (Chapter 25) |
|
Oct 20 |
EXAM II |
|
Oct 23 |
Deep Learning I (Chapter 26) |
|
Oct 27 |
Deep Learning II (Chapter 26) |
|
Oct 30 |
Support Vector Machines I (Chapter 21) |
|
Nov 03 |
Support Vector Machines II (Chapter 21) |
|
Nov 06 |
Probabilisitic Classification (Chapter 18) |
|
Nov 10 |
Classification Assessment (Chapter 22) |
|
Nov 13 |
EXAM III |
|
Nov 17 |
Representative-based Clustering (Chapter 13) |
|
Nov 20 |
Representative-based Clustering II (Chapter 13) |
|
Nov 24 |
Density-based Clustering (Chapter 15) |
|
Nov 27 |
NO CLASS (Thanksgiving) |
|
Dec 01 |
Spectral and Graph Clustering I (Chapter 16) |
|
Dec 04 |
Spectral and Graph Clustering II (Chapter 16) |
|
Dec 08 |
Itemset Mining (Chapter 8) |
|
Dec 11 |
EXAM IV |