Difference between revisions of "Spring 2023: Data Mining"
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===Tests and Quizzes=== | ===Tests and Quizzes=== | ||
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Revision as of 22:59, 31 January 2023
Contents
Logistics
- Class Timings: Wednesdays 1:00 pm - 3:00 pm (5th and 6th slot)and Thursdays 10:45 am - 12:45 pm (3rd and 4th slot)
- Classroom: R33
- Lab Timings: Mondays 8:45 am - 12:45 pm (1st - 4thslots)
- Labs: CS Lab 5
Course Overview
- As per the Delhi University Course Guidelines
Lectures
| Lecture | Topic | Lecture Slides | Readings |
|---|---|---|---|
| Unit1/Chapter1 | Introduction: 1.1 - What Is Data Mining? 1.2 Challenges 1.3 Data Mining Origins 1.4 Data Mining Tasks | Introduction.pdf | Chapter 1 (R1) |
Assignments and Tests
Class Assignments
- Assignment No. 1,
- Assignment No. 2,
Tests and Quizzes
- Test 1 :
- Test 2 :
Projects
- Project 1 :
- Project 2 :
- Project 3 :
- Project 4 :
- Project 5 :
- Project 6 :
- Project 7 :
- Project 8 :
- Project 9 :
- Project 10 :
Resources
Course Books:
- CB1: Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson Education.
References:
- R2: Data Mining: Concepts and Techniques, 3nd edition,Jiawei Han and Micheline Kamber.
- R3: Data Mining: A Tutorial Based Primer, Richard Roiger, Michael Geatz, Pearson Education 2003.
- R4: Introduction to Data Mining with Case Studies, G.K. Gupta, PHI 2006.
- R5: Insight into Data mining: Theory and Practice, Soman K. P., DiwakarShyam, Ajay V., PHI 2006
