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  • Lecture time: Friday: 13:30:00 - 14:20:00 ET
  • Lab time: Monday: 13:30:00 - 15:20:00 ET
  • Domain: University
  • Keywords: Data Cleaning, Factor Analysis, Student Experience, Student Life
  • Tools: Data Exploration, Python, R, Statistical Modeling, Technical Writing
  • Citizenship: Open to all students
Summary

Exploratory data analysis into the many factors that influence the student experience, GPA, and retention for Student Life.

  • Lecture time: Thursday: 12:30:00 - 13:20:00 ET
  • Lab time: Tuesday: 11:30:00 - 13:20:00 ET
  • Domain: Agriculture
  • Keywords: Clustering, Feature Extraction, NLP, Text Classification
  • Tools: Data Cleansing, Data Exploration, JMP/SAS, Python, Pytorch, R, Tensorflow, Web-scraping
  • Citizenship: Open to all students
Summary

1) Identify meta-level grouping factors/characteristics via text mining from relevant agronomic/biotech literature to map/reduce the variety naming space and better support agronomic insights. 2) Use NLP techniques to clean up the variety names.

  • Lecture time: Friday: 11:30:00 - 12:20:00 ET
  • Lab time: Monday: 11:30:00 - 13:20:00 ET
  • Domain: Agriculture
  • Keywords: AWS Cloud Services, Computer Vision, Machine Learning, Satellite Imagery, Spark, Wildlife Conservation
  • Tools: Computer Vision, Geospatial Data Analysis, Machine Learning, Radar Data, Satellite Imagery
  • Citizenship: Open to all students
Summary

Develop an automated approach to enroll customer acres and generate a profitability map in ArcGIS.

  • Lecture time: Monday: 15:30:00 - 16:20:00 ET
  • Lab time: Friday: 15:30:00 - 17:20:00 ET
  • Domain: Animal Health
  • Keywords: Animal Behavior, Computer Vision, IoT
  • Tools: Python, R, Shiny App
  • Citizenship: Open to all students
Summary

Utilize computer vision AI system to enable in-home pet identification and diagnostics

  • Lecture time: Monday: 11:30:00 - 12:20:00 ET
  • Lab time: Friday: 11:30:00 - 13:20:00 ET
  • Domain: University
  • Keywords: Pricing, Secondary Market Data, Stadium Mapping, Ticket Sales, Ticket Usage
  • Tools: Python, R, Tableau
  • Citizenship: Open to all students
Summary

The 22-23 projects will finalize current projects with live events to include populating the Ross-Ade stadium map with ticket sales data and game day scan data from both static files and auto generated .iqy files.