We decided to explore the recommendation of movies with a K cluster ML system by taking the tags of movies such as ratings, directors, and actors and determining the audiences that coincide with the systems. This is done with a database from tmbd that contains data from around 5,000 movies.
- Select 3 movies from our database
- Movie recommendation using ML Algorithm kmeans
- Implements LLMs to filter requests and provide feedback data
- Light and Dark mode enabled
- Available in all devices
streamlit_app
ββ home.py
ββ .streamlit
β ββ secrets.toml
β ββ gcloud.json
ββ algorithms
| ββ movie_model.pkl
| ββ moviesPredictor.py
ββ api
ββ assets
β ββ files
β ββ images
ββ pages
β ββ report_bug.py
β ββ match.py
ββ requirements.txt
- OpenAI API
- Streamlit
- Google Sheets API
- scipy
Deployed with: Streamlit Cloud