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https://github.com/luluw8071/content-filtering
Movie Recommendation | Content Filtering
https://github.com/luluw8071/content-filtering
algolia-api bagofwords content-based-recommendation cosine-similarity flask-application movie-recommendation stemming-porters tmbd-api vectorization
Last synced: 2 days ago
JSON representation
Movie Recommendation | Content Filtering
- Host: GitHub
- URL: https://github.com/luluw8071/content-filtering
- Owner: LuluW8071
- License: mit
- Created: 2023-11-10T09:26:02.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-22T12:49:38.000Z (12 months ago)
- Last Synced: 2023-11-22T13:44:49.939Z (12 months ago)
- Topics: algolia-api, bagofwords, content-based-recommendation, cosine-similarity, flask-application, movie-recommendation, stemming-porters, tmbd-api, vectorization
- Language: Jupyter Notebook
- Homepage:
- Size: 19.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
### Movie Recommendation
#### Dependencies
To install the required Python packages you can use the following command:
```bash
pip install -r requirements.txt
```
- Run `model.ipynb` & `dataset.ipynb`
- Edit `api.py`
- Create an account at Algolia
- Create your index and upload records of `movies_dataset.csv`
- Create an account at TMDb
- Get your API and edit on api.py
```
# TMDB API Key Auth
TMDB_API_KEY = '_______________'
# Algolia API Search
ALGOLIA_APP_ID = '____________'
ALGOLIA_API_KEY = '______________________'
ALGOLIA_INDEX_NAME = '_______________________'
```
*Note: Run ```py api.py``` with Test Cases 1 & 2 to check request*
- Run `app.py`
To run the app.py, load the dependecies requirements, edit `api.py` and use the following command:
```
py app.py
```
✨ Enjoy the demo
Feel free to send issues if you face any problem.
✨ Don't forget to star the repo :)