Semester Projects
| Title | Project Proposer | Description | Technologies | Status |
| NFL Big Data Bowl Competition | Luke Neuendorf (lneuendorf@wisc.edu) | I plan to compete in the NFL Big Data Bowl this year, in a non-undergraduate track. The competition details are usually released in mid-October. If there are other graduate students or undergraduate students interested in competing in a non-undergraduate track, feel free to reach out! | Python, R | Starting |
| Madison Restaurant Explorer | Ainesh Mohan (amohan28@wisc.edu) | A recommendation system that would take into consideration of user’s taste, budget, and location, and uses sentiment analysis to take reviews in from services like yelp. | Python, NLTK/spaCy, transformers, SQL, BeautifulSoup, frontend frameworks too for web/app development | Starting |
| Effect of stress on eating habits of College Students | Anubhav Choudhery (choudhery@wisc.edu) | Mental stress can change a person’s lifestyle. Its effect on sleeping and drinking habits is relatively well known and researched upon. However, mental stress could possibly change a person’s regular eating habits which in turn could lead to health issues. | Python, Google Colab, Anaconda/Kaggle | Starting |
| Wisconsin Football/Basketball Analytics | Shekhar Shah (sshah77@wisc.edu) | Our project is to assist football and basketball teams with useful analytics and predictive models to help coaches and players improve performance. We could have two different sections, one of them assisting with gameday strategy and preparation – providing advance reports and insights to coaches and staff before gameday as well as helping with gametime decisions, such as deciding whether or not to go for it on 4th down, or deciding which defensive substitution to make during the basketball games. The other section could assist with recruiting, where we could generate predictive models to see the chances a player commits to Wisconsin. Using machine learning techniques, we could set thresholds to visualize a particular recruit’s probability of exceeding those thresholds in performance once committing to Wisconsin. These ideas would only be the foundation, and with a larger team, we could build out a database and generate new, innovative ideas that can be implemented over a longer period of time. | R, Python, Machine Learning Techniques such as XGBoost, Random Forest, GLM etc. | Starting |
| StockSense Advisor | Gautam Agarwal (gagarwal8@wisc.edu) | Email Service that tracks invested stocks, studies stock trends and informs the user which stock needs attention | Starting |
if you wish to sign-up for a project reach out to the project proposer and remember to cc dotdatauw@gmail.vom