IMovie Recommender is a movie recommendation system built with the web2py framework using ML. For the backend, libaries such as pandas, numpy was used in Python for the calculation of recommendations. For the front-end, HTML/CSS/JS was used. It uses an algorithm called "Cosine Similarity" from a plethora of recommendation algorithms, to provide users with movie recommendations based on the ratings of one or multiple movies.
- Search filtering
- Personalized movie recommendations
- User-friendly interface
- A movie carousel
- Settings Page
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
To run the web application on your local machine, follow the following steps.
- First, download web2py from this link : https://mdipierro.pythonanywhere.com/examples/static/nightly/web2py_src.zip
- Second, download the Recommendations Model File: https://drive.google.com/file/d/17orEFW-9isAQJW4yriiaMwLGBkV_DVig/view?usp=share_link
- Place this file under the "\web2py\applications\movies\static" folder.
- [Optional] Finally, download the mid- quality posters for loading in the app: https://drive.google.com/file/d/1RGZgTpcRl68AMoASxpyC7LDRYsgd39bs/view?usp=share_link
- Extract the posters from the "posters.zip" file to the path "\web2py\applications\movies\static" folder.
- Open command prompt (windows 10) and type the following:
cd [directory where you extracted the file downloaded in step 1]
cd web2py
python web2py.py- A web2py Web Framework window will appear as shown below.
- For password, type 'root' or anything you prefer.
- Click "start server" and a new window will be loaded on your browser of choice.
- Now, go to this link on your browser or right-click on it here and "Open in New Tab" : http://127.0.0.1:8000/movies/static/htmlindex.html
- Done! Now you can start using the app as normal users would.