CSC 466: Knowledge Discovery From Data
Fall 2019

Instructor: Alexander Dekhtyar,, 14-210

Office Hours:
Who Where
Monday 10:10am - 11:00am Alex 14-210
Tuesday 9:10am - 11:00am Alex 14-210
Wednesday 9:10am - 11:00am Alex 14-210

Additional appoinments: send email.

Final Exam Date: Monday, December 13, 2019, 10:10 - 1:00pm

(note: there is no final exam, but we may use the time for course-related activities)

News and Notes

Course Materials

Syllabus Postscript PDF
Github Id Survey Survey
Jupyter Hub Login Page Log in with Gitgub Id
Spring 2018 Exam files Task1.ipynb, data1.csv Task2.ipynb, data5.csv Task3.ipynb, data8.csv


Lab 1 Due: September 27 (Friday) Insight From Data Postscript PDF Data [September 19, 2019]
Lab 2 Due: Association Rules Postscript PDF Data [September 27, 2019]
Lab 3 Due: October 14 / October 22 (Mondays) Supervised Learning (Classification) Postscript PDF Data [October 3, 2019]
Lab 4 Due: November 4 (Monday, 11:00am) Unsupervised Learning Postscript PDF Data [October 23, 2019]
Lab 5 Due: November 15 Information Retrieval/Text Mining Postscript PDF Data [November 2, 2019]
Lab 6 Due: November 25 Collaborative Filtering Postscript PDF Data [November 15, 2019]
Lab 7 Due: December 6 Link Analysis Postscript PDF Data [November 22, 2019]


Analytical Project Due: November 9/December 13 2018 Multiple Datasets Postscript PDF [November 2, 2018]
Ethics and KDD Assignment Due: December 13, 2019 Science Fiction Dystopia Story Postscript PDF [November 22, 2019]

Lab Data

Lecture Notes

Lecture 1 What is KDD? Postscript PDF PowerPoint(by Jonathan Ventura)
Lecture 2 Association Rules Mining: Apriori Postscript PDF PowerPoint(by Jonathan Ventura)
Lecture 3 Association Rules Mining: Apriori examples Postscript PDF
Lecture 4 Classification. Decision Trees Postscript PDF
Lecture 5 Classification: C4.5. example Postscript PDF
Lecture 6 Classification: Beyond C4.5. Postscript PDF
Lecture 7 Clustering: K-means Postscript PDF
Lecture 8 Distance Measures Postscript PDF
Lecture 9 Clustering: Hierarchical Postscript PDF
Lecture 10 Collaborative Filtering: Intro Postscript PDF
Lecture 11 Collaborative Filtering: Evaluation Postscript PDF
Lecture 12 Information Retrieval: measures, models Postscript PDF
Lecture 13 Information retrieval: extending VSM Postscript PDF
Lecture 14 Social Network/Graph Mining Postscript PDF
Lecture 15 PageRank:The Algorithm Postscript PDF
Lecture 16 PageRank: The Math Postscript PDF
Lecture 17 Community Discovery Postscript PDF
Lecture 18 Naive Bayes Postscript PDF

September 19, 2019, dekhtyar at