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: 10AM-11:50AM Mon/Thurs, Darrin 308

Instructor Office Hours: 12-1PM Mon/Thurs (Lally 209)

TAs (Office Hours):

Aitazaz Khan (Wed 12-1pm, Thur 1-2pm, AE118)

Syllabus: CSCI4390-6390 Syllabus




Assign2: CSCI4390-6390 Assign2, Due: 28th Sep

Assign1: CSCI4390-6390 Assign1, Due: 15th Sep

Class Schedule: Lectures

Tentative course schedule is given below. Lecture notes (in PDF) appear below, and the lecture videos ca n be accessed at the RPI's Mediasite Channel for CSCI4390.

Date Topic Lectures
Aug 28 Introduction & Data Matrix (Chapter 1) lecture1
Aug 31 Data Matrix/Numeric Attributes (Chapters 1 & 2) lecture2
Sep 05 (Tue) Numeric Attributes (Chapter 2) lecture3
Sep 07 PCA (Chapter 7) lecture4
Sep 11 PCA II and Discriminant Analysis (Chapters 7, 20) lecture5
Sep 14 Discriminant Analysis II, Gradient Descent (Chapter 20) lecture6
Sep 18 High Dimensional Data I (Chapter 6) lecture7
Sep 21 High Dimensional Data II, Linear Regression (Chap 6, 7) lecture8
Sep 25 Linear Regression II (Chapter 7)
Sep 28 Linear Regression III (Chapter 7)
Oct 02 Exam I
Oct 05 Support Vector Machines I (Chapter 21)
Oct 09 NO CLASS (Columbus Day)
Oct 12 Support Vector Machines II (Chapter 21)
Oct 16 Neural Networks I (Chapter 25)
Oct 19 Neural Networks II (Chap 25)
Oct 23 Deep Learning (Chapter 26)
Oct 26 Deep Learning II (Chap 25)
Oct 30 Classification Assessment (Chapter 22)
Nov 02 EXAM II
Nov 06 Representative-Based Clustering (Chapter 13)
Nov 09 Representative-Based Clustering
Nov 13 Density-based Clustering (Chapter 15)
Nov 16 Density-based Clustering II (Chapters 15)
Nov 20 Spectral Clustering (Chapters 16)
Nov 23 NO CLASS (Thanksgiving)
Nov 27 Spectral Clustering II (Chapter 16)
Nov 30 Clustering Validation (Chapters 17)
Dec 04 Wrapup