Recommendation System

Movie recommendation engine is a machine learning project which recommends user various movies based on what user has searched. The machine learning model calculates the similarity score between the movies using tags and based on that most similar movies are recommended.

Version - 0.0
Base Architecture

Starting Development Server:rocket:

• You need to have Python installed in your machine. Run this command python --version in your terminal/command prompt. If you get something like v3.10.4 then you have successfully installed python on your machine.:sparkles:
• Now download the zip file of the repository. Or use git clone <package-name>.:sparkles:
• Now open src>web>modelled-data directory and extract the modelled-data zip file here (make sure extracted file are in same directory with zip).
• Open a terminal in the src>web directory or you can simply open the folder inside vscode and open the integrated terminal. Then run pip install -r requirements.txt this will simply install all the required python modules.:sparkles:
• After the installation is finished run streamlit run app.py and wait for couple of seconds for You can now view your Streamlit app in your browser. this message to appear on terminal.:sparkles:
• Now open a browser and go to localhost:8501 and voila!!:fire::fire:

-Demo Video:

Start.web.app.mp4

Model Training

• You need to have Jupyter Notebook in your machine.
• Now open a terminal in src>main directory and then run jupyter notebook.
• Once your jupyter notebook is ready. Open Machine_Learning_Project.ipynb file and run all cells.
• voila!!:fire::fire: your modelled data is created and ready to use.
• Demo Video:

Start.jupyter.notebook.mp4

Initially it may take some time to load the website.

Hosted Link: https://weflix.herokuapp.com/