Thesis Project

Fake News Detection using Machine Learning is a comprehensive project that utilizes machine learning and natural language processing techniques to identify and classify fake news articles. The project includes data analysis, model training, and a real-time web application for detecting fake news.

A web application to detect fake news headlines based on CNN model with TensorFlow and Flask.

A Fake News Detection System built with Neural Networks.

fake news classification using MLP, LSTM and transformer

Fake News Detection End to End project with deployment 🔥. distinguishes between authentic and fake news, contributing to media credibility. 🚀

Bengali/Bangla Fake Review Detection Dataset

In this project, we have built a classifier model using NLP that can identify news as real or fake. For this purpose, we have used data from Kaggle.

Projects completed during internship with code.

As the Covid-19 virus quickly spreads across the globe, the world is not just dealing with a “Pandemic” but also an “Infodemic”. Considering that the world is on the brink of disaster, it is paramount to validate the authenticity of dubious information. We present in this project a web application whose detection process is based on the assembla…

Fake News Detection with a Bi-directional LSTM in Keras

Detection of Fake Product Reviews Using NLP Techniques

API REST for detecting if a text correspond to a fake news or to a legitimate one. It's served using Flask and uses a fine-tuned BERT model.

Fake News Detection Using Social Media User Network and Engagement Features

we will focus on text-based news and attempt to develop a model that will assist us in determining if a certain piece of news is fake or not.

Fake news Detection using Machine Learning