CSCE41403 Schedule

Schedule for CSCE 41403, Section 1: Data Mining

(This will be changed frequently. Please check this page before class every week.)

Date	Topics Covered	Reading Assignment(before class)	Handout
Aug 19	Class overview	Chapter 1 A tour of machine learning algorithms Top 10 data mining algorithms	DS overview ch1
Aug 21	Data mining programming	Machine learning in Python	DataMiningPython Code link
Aug 26	Classification	Chapter 8 (skip 8.4)	ch8 probability Bayesian example entropy (optional) Homework (solution)
Sept 2
Sept 4
Sept 9	Logistic regression	Logistic regression	Logistic regression kNN
Sept 11
Sept 16	Introduction to foundation models		guest lecture on VLMs
Sept 18 (no lecture)	Project implementation
Sept 23	Mining frequent patterns, associations and correlations	Chapter 6 (skip 6.2.3-6.2.6)	ch6 Homework (solution)
Sept 25
Sept 30	Cluster analysis	Chapter 10	k-means ch10
Oct 2
Oct 7	Classification: Advanced methods	Chapter 9	ch9 Bayesian Network BN exercise
Oct 9	Midterm		review questions midterm (solution)
Oct 14	Fall break
Oct 16	SVM	SVM-reading	SVM
Oct 21
Oct 23	Graph Mining	Link analysis	Social network analysis  Homework (solution)
Oct 28
Oct 30
Nov 4	Dimension Reduction	Chapter 3	ch3 PCA
Nov 6 (no lecture)	Project implementation
Nov 11 Nov 13	Privacy preserving data mining	Differential Privacy	Privacy preserving data mining
Nov 18	Project presentation	7 minute (including 1-minute Q/A) for each presentation	G1, G2, G3, G4, G6, G7, G13
Nov 20	Project presentation	7 minute (including 1-minute Q/A) for each presentation	G5, G8, G11, G12, G14, G15, Tyler, Eclam
Nov 25	Causal modeling and inference	Judea Pearl’s tutorials
Dec 2	Big Data Analytics	MapReduce MRSQL	MapReduce
Dec 4	Deep learning models	Tutorial 1 and 2 Review	DL Introduction DL Advanced DLTools
Dec 9 (10:15am-12:15pm)	Final exam