Inspiration

Friends who look confused whenever they look at a menu. Also, our foodie friends want to try something new every time.

What it does

Recommends food when you take a snap of a menu from your favorite restaurant!

How we built it

UI: Flask (Python) Back End: Content-Based Filtering Algorithm to recommend the food from menu

Challenges we ran into

We had no experience in using machine learning algorithms or any type of filtering algorithm. We had to figure out how the algorithm actually works so we can work it on our dataset. Another challenge was connecting the front end and back end. However the most hard one was clearing and arranging dataset so that we can apply our ML algorithm.

Accomplishments that we're proud of

Designing a sleek and smooth front end Connecting back and front end Designing our first ML algorithm that recommends food based on User's preferences and history

What we learned

Learned to apply ML algorithm Learned about K-means, collaborative filtering, content based filtering, and similarity matrix Learned to use the flask to create front end using python

What's next for Foodio

adding another feature called nutrition values and recommending healthy food

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