Datathon 2021
ABOUT Datathon:
Datathon is a competition focused on using data science techniques to solve a real-world issue in any discipline. Similar to hackathons, participants are responsible for creating a product that can solve practical problems. Final products include, but are not limited to, machine learning models, insights from statistical analysis, and business solutions based on predictive models. The competition took place in mid-October 2021 and was open for any UW-Madison students.
RULES
Each team should consist of 1-4 members.
Each project must utilize at least one dataset and must demonstrate appropriate use of data science methods.
All work must be conducted by the team members. The team may ask provided mentors for guidance, but not for direct solutions.
We believe in the importance of respect for all ideas and opinions. Any form of harassment will result in exclusion from the datathon.
WINNERS!
Winner- Major Explorer
By- Carrie Lu, Jing Kai Ong, Siyang Peng
Learn more about what classes you should take for additional majors!
1st Runner Up- Lifeline
By- Geoffrey Xue, Matthew Zapodeanu, Ruohe Zhou, Aiden Cohen
A data science driven solution for diagnosing healthcare problems before they start becoming problematic
2nd Runner Up & Best Presentation- Ungerrymanderrer
By- Joshua Hopwood, Jeremy Parker, Vasudha Khanna, Mohamed Almarzooqi
Ungerrymandering our way to One-Person-One-Vote
Google Cloud API Challenge Runner Up- Car identification CNN model
By- Trispedia Zhu, Yuan Tian, Xiaotian Wang
Never mistake any specific car
Most Popular Hack- Helping Hands
By- Agam Goyal, Shreya Jagadeshwaran, Shivansh Aggarwal
Social media posts sentiment analysis using NLP to predict suicidal thoughts “We are here for you!”
Our Sponsors
At Corteva Agriscience we grow progress by putting farmers and consumers at the heart of agriculture, to help reshape the industry for the 21st century. We believe that the future of farming depends on aligning the food chain from end to end so that we can work together to build agriculture into an industry that is more financially secure, sustainable, innovative, and responsive. We are helping to shape an industry better able to understand and react to global market demands, that can effectively harness science, technology, and innovation to optimize productivity, and which has the know-how and resources to help chart its own long-term success in the face of challenge and change.
As an Electronic Health Record (EHR) software company, Epic supports healthcare organizations across the globe. These healthcare organizations gather a huge amount of patient data. Epic’s program called Cosmos brings together healthcare data from across the Epic community, pulling together over 100 million longitudinal patient records from over 100 contributing organizations across the United States. To build Cosmos, Epic had to find solutions to a number of technical problems and governance needs. These solutions had to work at scale and across disparate pre-existing customer systems with minimal configuration. The data must be reviewed to make sure it is high quality, consistent, and timely and our processes vetted to ensure the data is protected. Finally, we needed tools that enable researchers to dive into the data and turn it into knowledge.
The Machine learning research and innovation group at American Family Insurance aims at providing innovative and efficient AI-and -data-science-inspired solutions to the enterprise. We coordinate ML and AI research with labs and universities and explore how recent advances in the area could impact problems relevant to the insurance domain.
Analytics at John Deere encompasses a wide range of technologies and business areas including computer vision for autonomy, forecasting sales of equipment, customer support (expert alerts to identify potential problems), John Deere Finance (customer risk profiling and segmentation), market analysis, and machine learning for optimizing machinery. Our data analytics practitioners primarily use Python, R, and SQL as well as a significant amount of work with big data platforms like Spark and Databricks.
Thomson Reuters is a content-driven technology company with over a century of experience curating and classifying data and supporting professionals in complex domains that move society forward.
Embedded in this legacy is our team of AI-focused engineers, research and data scientists, and designers who work with some of the most comprehensive and richly enhanced legal, tax, and other professional datasets in the world.
Join us in building the next generation of AI-enabled solutions for legal, tax & accounting, risk, fraud and compliance, and media.
We are hiring in Bangalore, Zug, London, Toronto, and Minneapolis-St. Paul.
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.