Association Mining for Machine Learning
This course covers the working Principle of Association Mining and its various concepts like Support, Confidence, and Life in a very simplified manner. This course discusses about Naive Algorithm and Apriori Algorithm for finding Association Mining rules by taking lot of examples. All of these algorithms has been explained by taking working examples.
Who this course is for:
- Students taking Machine Learning or Data Mining Course
- Machine Learning Enthusiast
- Students preparing for placement tests and interviews
- 10:31Association Mining: Concepts and Applications
- 12:35Support and Confidence
- 10:09Concept of Lift
- 10:38Assignment for Support, Confidence and Lift
Parteek Bhatia is Professor in the Department of Computer Science and Engineering and Former Associate Dean of Student Affairs at Thapar Institute of Engineering and Technology, Patiala. At present he is on sabbatical at Tel Aviv University, Israel and acting as Visiting Professor at LAMBDA Lab, TAU. He is recipient of Young Faculty Research Fellowship from Ministry of Electronics & Information Technology, Govt. of India.
He has more than twenty years of academic experience. He has completed his Ph.D on "UNL Based Machine Translation System for Punjabi Language" from Thapar University. He has published more than 75 research papers and articles in Journals, Conferences and Magazines of repute. His research work with UNDL foundation, Geneva, Switzerland involved participation in Advanced UNL School at Alexandria, EGYPT in 2012 and at Geneva, Switzerland in 2013 and 2014. He is a winner of Gold Medal at International competition UNL Olympiad II,UNL Olympiad III and UNL Olympiad IV conducted by UNDL Foundation in year 2013 and 2014.
He has authored multiple text books including Data Mining and Data Warehousing: Principles and Practices from Cambridge University press, Simplified Approach to DBMS, Simplified Approach to Visual Basic and Simplified Approach to Oracle. He is acting as Principal Investigator on several projects funded by Government of India.