Fake News Detection

Abstract

1. Introduction

In this project, we have used various natural language processing techniques and machine learning algorithms to classify fake news articles using sci-kit libraries from python.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

2. Objective

Fake News Detection in Python

This project demonstrates how Jupyter Notebook, Python can be applied to a real-world AI & Machine Learning problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
• pip for dependencies
• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/nishitpatel01/Fake_News_Detection.git
cd Fake_News_Detection

1. The first step would be to clone this repo in a folder in your local machine. To do that you need to run following command in command prompt or in git bash
2. This will copy all the data source file, program files and model into your machine.
3. If you have chosen to install anaconda then follow below instructions
4. Once you are inside the directory call the prediction.py file, To do this, run below command in anaconda prompt.
5. After hitting the enter, program will ask for an input which will be a piece of information or a news headline that you want to verify. Once you paste or type news headline, then press enter.
6. If you have chosen to install python (and did not set up PATH variable for it) then follow below instructions:
7. After you clone the project in a folder in your machine. Open command prompt and change the directory to project directory by running below command.
8. Locate python.exe in your machine. you can search this in window explorer search bar.

$ git clone https://github.com/nishitpatel01/Fake_News_Detection.git

cd C:/your cloned project folder path goes here/

python prediction.py

cd C:/your cloned project folder path goes here/

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Deploy the model as a web app with Streamlit, Flask or FastAPI
• Compare against an additional model and report the metric difference
• Add explainability (SHAP / Grad-CAM)

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What dataset does the project use and how was it pre-processed?
2. Which algorithm / model architecture is used and why was it chosen over alternatives?
3. How are training and testing data split, and how is overfitting avoided?
4. Which evaluation metrics (accuracy, precision, recall, F1) are reported and what do they mean here?
5. How would you deploy this model for real users?

9. Source Code & License

This project is developed by nishitpatel01 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.