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Data Mining Project

Data Mining Project

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8.1/10 (Our Score)
Product is rated as #242 in category Data Science

Note: You should complete all the other courses in this Specialization before beginning this course. This six–week long Project course of the Data Mining Specialization will allow you to apply the learned algorithms and techniques for data mining from the previous courses in the Specialization, including Pattern Discovery, Clustering, Text Retrieval, Text Mining, and Visualization, to solve interesting real–world data mining challenges. Specifically, you will work on a restaurant review data set from Yelp and use all the knowledge and skills you’ve learned from the previous courses to mine this data set to discover interesting and useful knowledge. The design of the Project emphasizes: 1) simulating the workflow of a data miner in a real job setting; 2) integrating different mining techniques covered in multiple individual courses; 3) experimenting with different ways to solve a problem to deepen your understanding of techniques; and 4) allowing you to propose and explore your own ideas creatively. The goal of the Project is to analyze and mine a large Yelp review data set to discover useful knowledge to help people make decisions in dining. The project will include the following outputs: 1. Opinion visualization: explore and visualize the review content to understand what people have …

Instructor Details

Jiawei Han is Abel Bliss Professor in the Department of Computer Science at the University of Illinois. He received his Ph.D. in Computer Sciences at University of Wisconsin in 1985. He worked as assistant professor in Northwestern University in 1986-1987 and as assistant, associate, full and university chair professor in Simon Fraser University in 1987-2001 before joining UIUC in 2001. He has been researching into data mining, information network analysis, and database systems, and their various applications, with over 600 publications. He served as the founding Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data (TKDD) (2007-2012). Jiawei has received ACM SIGKDD Innovation Award (2004), IEEE Computer Society Technical Achievement Award (2005), IEEE Computer Society W. Wallace McDowell Award (2009), Daniel C. Drucker Eminent Faculty Award at UIUC (2011), and Excellence in Graduate and Professional Teaching Award at UIUC (2012). He is a Fellow of ACM and a Fellow of IEEE. He has been serving as the Director of Information Network Academic Research Center (INARC) supported by the Network Science-Collaborative Technology Alliance (NS-CTA) program of U.S. Army Research Lab since 2009. His co-authored textbook "Data Mining: Concepts and Techniques" (Morgan Kaufmann) has been adopted popularly as a textbook worldwide.

Specification: Data Mining Project

Duration

17 hours

Year

2017

Certificate

Yes

Quizzes

No

5 reviews for Data Mining Project

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  1. Rodrigo C C

    Very good course!

    Helpful(0) Unhelpful(0)You have already voted this
  2. Gary C

    Sloppy final project, missing submissions links. Sections are no longer consistent. Nobody from UIUC responds, and nobody has in what seems like a year. A useless course.

    Helpful(4) Unhelpful(0)You have already voted this
  3. Ivan A

    The project help me to practice the whole specialization algorithms and techniques.

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  4. Hernan C V

    Awesome!

    Helpful(0) Unhelpful(0)You have already voted this
  5. GANG L

    Course content is excellent, but lack of support.

    Helpful(3) Unhelpful(0)You have already voted this

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