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 330

Instructor Office Hours: 12-1PM Mon/Thurs

TAs (Office Hours):

Qitong Wang (1-3PM Wed, AE118)

Dhruva Narayan (12:30-1:30PM Tue, Fri, AE118)

Syllabus: CSCI4390-6390 Syllabus




Assign3: CSCI4390-6390 Assign3, Due: 30th Sep

Assign2: CSCI4390-6390 Assign2, Due: 23rd Sep

Assign1: CSCI4390-6390 Assign1, Due: 9th Sep

Class Schedule: Lectures

Tentative course schedule is given below.

Date Topic Lectures
Aug 29 Introduction & Data Matrix (Chapter 1) lecture1
Sep 01 Data Matrix/Numeric Attributes (Chapter 2) lecture2, lecture2 video
Sep 06 (Tue) Numeric Attributes (Chapter 2) lecture3, lecture3 video
Sep 08 PCA (Chapter 7) lecture4, lecture4 video
Sep 12 PCA II (Chapter 7) lecture5, lecture5 video
Sep 15 High Dimensional Data (Chapter 6) lecture6, lecture6 video
Sep 19 High Dimensional Data II (Chapter 6) lecture7, lecture7 video
Sep 22 Kernel Methods I (Chap 5) lecture8, lecture8 video
Sep 26 Kernel PCA (Chapter 7)
Sep 29 Linear Regression I (Chapter 23)
Oct 03 EXAM I
Oct 06 Linear Regression II (Chapters 23)
Oct 10 NO CLASS (Columbus Day)
Oct 13 Support Vector Machines I (Chapter 21)
Oct 17 Support Vector Machines II (Chapter 21)
Oct 20 Logistic Regression (Chapter 24)
Oct 24 Neural Networks (Chapter 25)
Oct 27 Neural Networks II (Chap 25)
Oct 31 Deep Learning (Chapter 26)
Nov 03 EXAM II
Nov 07 Probabilistic Classification (Chapter 18)
Nov 10 Representative-based Clustering (Chapter 13)
Nov 14 EM-Clustering (Chapter 13)
Nov 17 Density-based Clustering (Chapter 15)
Nov 21 Spectral Clustering (Chapter 16)
Nov 24 NO CLASS (Thanksgiving)
Nov 28 Classification Assessment (Chapter 22)
Dec 01 Classification Assessment II (Chapter 22)
Dec 05 Clustering Validation (Chapter 17)