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Data Mining Project

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HomeData ScienceData Analysis

Data Mining Project

University of Illinois at Urbana-Champaign

About this course: 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 said in those reviews. 2. Cuisine map construction: mine the data set to understand the landscape of different types of cuisines and their similarities. 3. Discovery of popular dishes for a cuisine: mine the data set to discover the common/popular dishes of a particular cuisine. 4. Recommendation of restaurants to help people decide where to dine: mine the data set to rank restaurants for a specific dish and predict the hygiene condition of a restaurant. From the perspective of users, a cuisine map can help them understand what cuisines are there and see the big picture of all kinds of cuisines and their relations. Once they decide what cuisine to try, they would be interested in knowing what the popular dishes of that cuisine are and decide what dishes to have. Finally, they will need to choose a restaurant. Thus, recommending restaurants based on a particular dish would be useful. Moreover, predicting the hygiene condition of a restaurant would also be helpful. By working on these tasks, you will gain experience with a typical workflow in data mining that includes data preprocessing, data exploration, data analysis, improvement of analysis methods, and presentation of results. You will have an opportunity to combine multiple algorithms from different courses to complete a relatively complicated mining task and experiment with different ways to solve a problem to understand the best way to solve it. We will suggest specific approaches, but you are highly encouraged to explore your own ideas since open exploration is, by design, a goal of the Project. You are required to submit a brief report for each of the tasks for peer grading. A final consolidated report is also required, which will be peer-graded.


Created by:  University of Illinois at Urbana-Champaign
University of Illinois at Urbana-Champaign

  • Jiawei Han

    Taught by:  Jiawei Han, Abel Bliss Professor

    Department of Computer Science

  • ChengXiang Zhai

    Taught by:  ChengXiang Zhai, Professor

    Department of Computer Science

  • John C. Hart

    Taught by:  John C. Hart, Professor of Computer Science

    Department of Computer Science
Basic Info
Course 6 of 6 in the Data Mining Specialization
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.6 stars
Average User Rating 4.6See what learners said
Syllabus
WEEK 1
Orientation
In this module, you will become familiar with the course, your instructor, your classmates, and our learning environment.
1 video, 6 readings
  1. Video: Welcome to the Data Mining Project!
  2. Reading: Orientation Overview
  3. Reading: Syllabus
  4. Reading: About the Discussion Forums
  5. Reading: Updating Your Profile
  6. Reading: MeTA Installation and Overview
  7. Reading: Data Set and Toolkit Acquisition
  8. Discussion Prompt: Getting to Know Your Classmates
Task 1 - Exploration of a Data Set
2 readings
  1. Reading: Task 1 Overview
  2. Reading: Task 1 Rubric
Graded: Task 1 Submission
WEEK 2
Task 2 - Cuisine Clustering and Map Construction
2 readings
  1. Reading: Task 2 Overview
  2. Reading: Task 2 Rubric
Graded: Task 2 Submission
WEEK 3
Task 3 - Dish Recognition
2 readings
  1. Reading: Task 3 Overview
  2. Reading: Task 3 Rubric
Graded: Task 3 Report Submission
WEEK 4
Task 4 & 5 - Popular Dishes and Restaurant Recommendation
2 readings
  1. Reading: Task 4 and 5 Overview
  2. Reading: Task 4 and 5 Rubric
Graded: Task 4 and 5 Submission
WEEK 5
Task 6
2 readings
  1. Reading: Task 6 Overview
  2. Reading: Task 6 Rubric
Graded: Task 6 Report Submission
WEEK 6
Final Report
2 readings
  1. Reading: Final Report Instructions
  2. Reading: Final Report Rubric
Graded: Final Report Submission

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Creators
University of Illinois at Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Pricing
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Earn a shareable Course Certificate

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Ratings and Reviews
Rated 4.6 out of 5 of 17 ratings
Hernan Ceferino Vazquez

Awesome!

Ivan Atanasov

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

Rodrigo Carvalho Costa

Very good course!



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