Wells Fargo's Campus Analytics Challenge: Live Green and Live Happy

One of Wells Fargo’s priorities is to promote environmental sustainability, which includes accelerating the transition to a low-carbon economy. Taking individual actions can encourage collective responsibility to help achieve this. Using machine learning, create a data product to help individuals optimize the balance between their carbon footprint and quality of life. The data gives a peek into the lives of 1,000 individuals who rated several everyday activities (taking a long shower, driving a car, etc.) on a scale of 1-100 based on how important those activities are to their daily lives.

The goal of this project is to create a machine learning algorithm that minimizes carbon footprint for each customer while maintaining their total quality of life.

• Written description of how the data product succeeds mathematically in minimizing an individual’s carbon footprint with minimal negative impact on their utility
• Explain why the data product created is a good example of machine learning in action
• General idea of how individuals would interface eg. a visual representation of the app
• Documented code that is operational and can be run using the data provided

Rules of the Competition Campus-Analytics-2018-Challenge-LONG-Rules-Final.docx

• Nick (@odintech3)
• Spandana (@spandanasudalagunta)
• Tina (@davinia1991)
• Prof. Murali Shanker (@mshanker1)