Do Sock Event Recommender

Inspiration

• There are a lot of societies in Durham so there are too many events to keep up with and keep track of. So we wanted to create a tool to help students be informed on different events and attend them.

What it does

• Recommends users future Durham society events that they can go to

How we built it

• We followed the collaborative filtering model and built it using Python and k-NN algorithm to find similar users and recommend events.

Challenges we ran into

• Data cleaning
• Creating the machine learning algorithm
• Merging different parts of the project from different team members together

Accomplishments that we're proud of

• Becoming more competent with machine learning and data science libraries

What we learned

• Different models of filtering and machine learning algorithms
• Using different Python libraries and tools

What's next for Recommender System Chain Event

• Create a web scraper to extract data about events in Durham
• To create a user interface and publish it online
• Build a website for students to use

Built With

• csv
• icalendar
• numpy
• pandas
• python
• scikit-learn
• seaborn