Fake News Detection

Fake news Detector using python and its various libraries like numpy pandas scikit-Learn ....etc

## :fire: Features - Legit and large amount of Data set from kaggle - Performed Data Preprocessing for better Accuracy - Performed Stemming on the data set - Performed vectorization technique on the data to convert textual data to numeric form - More Accuracy (97.90%) - Predicted the fake news with the help of Logistic Regression Technique ## :bulb: Built Using - [**Python**](https://www.python.org/) - [**Pandas**](https://pandas.pydata.org/) - For using the data Frames, reading CSV (Comma Seperated Value) file ...etc - [**NLTK**](https://www.nltk.org/) - For performing stemming in the data set - [**Scikit-Learn**](https://scikit-learn.org/) - For using various machine Learning Algorithm ## Instructions to run 1. Git clone this repository 2. ```pip install -r requirements.txt ``` to install all the dependencies 3. [**Download Data Set**](https://www.kaggle.com/c/fake-news/data?select=train.csv) 4. ```Fake_News_Prediction.ipynb``` 5. _now your app is up and running_ ## License Distributed under the MIT License. See `LICENSE` for more information. ## Contributing Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are **greatly appreciated**. 1. Fork the Project 2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`) 3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`) 4. Push to the Branch (`git push origin feature/AmazingFeature`) 5. Open a Pull Request

with :heart: by Avinash Kumar Jha