Inspiration
We noticed that college students had issues with meeting daily nutrition guidelines set by the FDA.
What it does
To help more students reach the daily value goals set by the FDA we created a program that calculates the calories of what an individual has eaten and recommends them a food item to help them reach their daily value limit.
How we built it
NutriScholar was programmed using python with the help of existing libraries like SKlearn, pandas, and fuzzyWuzzy.
Challenges we ran into
Implementing the ML-based libraries.
Accomplishments that we're proud of
Learning more about AI and how we can implement it into our code to solve a problem more efficiently.
What we learned
We learned how to plan a project, and then create plans that then can be executed to make finished project. We also learned how to work in a team to create a program that has multiple elements.
What's next for NutriScholar
Adding new features that can include a fitness component to help individuals know how many calories they need to burn to get under the daily value recommended.
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