Description as a Tweet:

What in your life are you grateful for? Daily Gratitude helps you acknowledge the positive each day and receive personalized summaries based on your submissions.


We have both been getting into journaling and finds that it puts us in a good mood for that day. Reminding yourself what you are thankful for trains your brain to look for the positives.

What it does:

Our project allows a user to submit daily "gratitudes" of things they are thankful for. We then use topic modeling to extract the most prevalent recipients of gratitude (for example: friends, family, coffee...). On a rough day, the user can ask for reminders of what they are most grateful for.

How we built it:

We built out app in Django and used gensim and spacy to build an LDA topic model.

Technologies we used:

  • Python
  • Django
  • AI/Machine Learning

Challenges we ran into:

We have never used Django before or done front end work. Downloading nlp dependencies posed challenges as well as they are cumbersome.

Accomplishments we're proud of:

We are proud of what we have accomplished in such a short time and seeing the topic models was rewarding.

What we've learned:

We learned the basics of Django and unsupervised learning libraries.

What's next:

Separating the "documents" to allow multiple runs of the topic model. Also, implementing more application logic like routing to have a complete app.

Built with:

Django, python, gensim, html, spacey

Prizes we're going for:

  • Fujifilm Instax Mini 11 Instant Film Camera, Sky Blue
  • Cash prizes: $1,000 total to first place team; $500 total to second place team; $200 to third place team
  • Nintendo Switches
  • Apple AirPods 3rd Gen
  • Bose Headphones
  • Meta Portals

Team Members

Abigail Elliott
Adi Geva

Table Number

Table TBD