RedditFlairPredictor

A Web Application to predict Reddit Flairs

Deployed and live at

Heroku - Reddit Flair Predictor

Directory Structure

This is a Flask Web Application set-up for hosting on Heroku servers.

1. [App.py] - This is the main app outlet application
2. [requirements.txt] - Contains Dependencies
3. [Jupyter Notebooks] - Folder which contains all the scripts
4. [Helper.py] - This is the application which is called to predict flair.
5. [Procfile] - Needed to setup Heroku.
6. [Templates] - Contains all static pages.
7. [Runtime] - To point Heroku with the required python version
8. [nltk.txt] - Used to download Nltk resources
9. [Trained Data] - Contains trained data and models

Project Execution

1. Open the Terminal.
2. Download the Repo.
3. Ensure that Python3 and pip is installed on the system.
4. Create a virtualenv by executing the following command: virtualenv -p python3 env.
5. Activate the env virtual environment by executing the follwing command: source env/bin/activate.
6. Enter the cloned repository directory and execute pip install -r requirements.txt.
7. Enter python shell and import nltk. Execute nltk.download() and exit the shell.
8. Add a .env and add required environment variables.
9. Now, execute the following command: python app.py and it will point to the localhost with the port.
10. Hit the IP Address on a web browser and use the application.

Process

Went through various documentation and refrence links to understand the complete process.

1. Extracted the data
2. Cleaned and processed the data.
3. Selected the best model using scaled pipe.
4. Created models and chose the best model with highest accuracy

Accuracy

0.57821721