https://github.com/jocelynvelarde/moviematch
Select 3 movies and we will provide you with our recommendation using K-means. Type in how you felt and we will take that into consideration for future instances.
https://github.com/jocelynvelarde/moviematch
gsheets kmeans machine-learning openai sentiment-analysis streamlit
Last synced: 28 days ago
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Select 3 movies and we will provide you with our recommendation using K-means. Type in how you felt and we will take that into consideration for future instances.
- Host: GitHub
- URL: https://github.com/jocelynvelarde/moviematch
- Owner: JocelynVelarde
- License: mit
- Created: 2024-02-13T13:47:43.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-02-15T17:56:40.000Z (over 2 years ago)
- Last Synced: 2025-01-07T17:17:27.610Z (over 1 year ago)
- Topics: gsheets, kmeans, machine-learning, openai, sentiment-analysis, streamlit
- Language: Jupyter Notebook
- Homepage: https://movierecc.streamlit.app/
- Size: 11 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Movie Matcher with Sentiment Analysis 🚀
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.
## Authors
- [@JocelynVelarde](https://github.com/JocelynVelarde)
- [@Diego785xd](https://github.com/Diego785xd)
## Features
- 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
## Structure
```bash
streamlit_app
├─ home.py
├─ .streamlit
│ └─ secrets.toml
│ └─ gcloud.json
├─ algorithms
| └─ movie_model.pkl
| └─ moviesPredictor.py
├─ api
├─ assets
│ └─ files
│ └─ images
├─ pages
│ └─ report_bug.py
│ └─ match.py
└─ requirements.txt
```
## Tools
- OpenAI API
- Streamlit
- Google Sheets API
- scipy
Deployed with: Streamlit Cloud
## Demo
[YouTube](https://www.youtube.com/watch?v=M9DtZs3MAUk&t=4s)
## License
[MIT](https://choosealicense.com/licenses/mit/)