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.

Home Page:https://movierecc.streamlit.app/

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Movie Matcher with Sentiment Analysis πŸš€

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.

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Authors

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

streamlit_app 
β”œβ”€ home.py
β”œβ”€ .streamlit
β”‚   └─ secrets.toml
β”‚   └─ gcloud.json
β”œβ”€ algorithms
|  └─ movie_model.pkl
|  └─ moviesPredictor.py
β”œβ”€ api
β”œβ”€ assets
β”‚  └─ files
β”‚  └─ images
β”œβ”€ pages
β”‚  └─ report_bug.py
β”‚  └─ match.py
└─ requirements.txt

Tools

  • OpenAI API
  • Streamlit
  • Google Sheets API
  • scipy

Deployed with: Streamlit Cloud

Demo

YouTube

License

MIT

About

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://movierecc.streamlit.app/

License:MIT License


Languages

Language:Jupyter Notebook 99.1%Language:Python 0.9%