Our project was inspired by a conversation on the homogeneity of the social media market as well as the severe lack of platforms for people to purely engage in intellectual pursuits. As a group of self-taught learners, we wanted to create a space where people would be able to share and collect learning resources such as books, articles, and Ted Talks with the idea that people would be able to learn alongside their friends.

What it does

Creates a social media space where users can easily share and recommend scholarly information.

How we built it

We used Python to build the machine learning back-end and website front-end.

Challenges we ran into

There were issues with the machine learning algorithm having an extremely high RMSE score.

Accomplishments that we're proud of

Building a user based collaborative filter recommendation system with a 4% margin of error.

What we learned

How to properly use Python and its libraries to create a cohesive feature of a future social media application.

What's next for Didactive

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