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.

Inspiration:

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:

  • HTML/CSS
  • 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