ECE 657A - Data and Knowledge Modeling and Analysis
To be announced
Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.
Data Structures and Algorithms, Probability, or consent of instructor.
- 35% Assignments
- 30% Exams
- 35% Project: (5% Proposal, 10 % presentation, 20% report)
- Data types, sources, nature, scales and distributions
- Data representations, transformation, dimensionality reduction and normalization
- Classification: Statistical based, Distance based, Decision based.
- Clustering: Partition-based, Hierarchical, Model and Density based, others.
- Retrieval and Mining: Similarity measures and matching techniques.
- Knowledge discovery in data: Association rules mining, web mining, text mining.
- Performance measures and tools: Statistical Analysis, Validity and Assessment Measures.
There is no required textbook. But most of the course is based on the following books and will be useful to take a look at them, especially Dunham and Duda.
- Margaret Dunham, Data Mining Introductory and Advanced Topics, ISBN: 0130888923, Prentice Hall, 2003.
- R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification (2nd ed.), John Wiley and Sons, 2001.
- Jiawei Han, Micheline Kamber & Jian Pei, Data Mining: Concepts and Techniques, 3rd ed, Morgan Kaufmann Publishers, May 2011.
- A. K. Jain and R.C. Dubes, Algorithms for Clustering Data, ISBN: 0-13-022278-x, Prentice Hall, 1988.
- P. Cohen, Empirical Methods for Artificial Intelligence, ISBN:0-262-03225-2, MIT Press, 1995.
Papers and electronic references will be made available on the course website which is on LEARN.
Recipe for success
Attend lectures. Do complementary work at home. Ask questions. Have fun.
Policy and Rules
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