Difference between revisions of "Spring 2023: Data Mining"

Revision as of 22:54, 31 January 2023

Class Timings: Wednesdays 1:00 pm - 3:00 pm (5^th and 6^th slot)and Thursdays 10:45 am - 12:45 pm (3^rd and 4^th slot)
Classroom: R33
Lab Timings: Mondays 8:45 am - 12:45 pm (1^st - 4^thslots)
Labs: CS Lab 5

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)

R1: Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson Education.
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 20065. Insight into Data mining: Theory and Practice, Soman K. P., DiwakarShyam, Ajay V., PHI 2006

@@ Line 36: / Line 36: @@
 == Resources ==
-* '''R1''': Learning PHP, MySQL, JavaScript, CSS & HTML5, (Robin Nixon), 3rd Edition, O’Reilly Media. <br>
+* '''R1''': Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson Education. <br>
-* '''R2''': JavaScript and JQuery – Interactive Front-end Web Development, (Jon Duckett), John Wiley and Sons, Inc. <br>
+* '''R2''': Data Mining: Concepts and Techniques, 3nd edition,Jiawei Han and Micheline Kamber. <br>
-* '''R3:''' Web Design with HTML and CSS Digital Classroom, (Jeremy Osborn, Jemmifer Smith and AGI Creative Team), Wiley Publishing, Inc.
+* '''R3''': Data Mining: A Tutorial Based Primer, Richard Roiger, Michael Geatz, Pearson Education 2003. <br>
+* '''R4''': Introduction to Data Mining with Case Studies, G.K. Gupta, PHI 20065. Insight into Data mining: Theory and Practice, Soman K. P., DiwakarShyam, Ajay V., PHI 2006