A Django webapp that detects fake news with Machine Learning.

This advanced python project of detecting fake news deals with fake and real news. Using sklearn, we build a TfidfVectorizer on our dataset. Then, we initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.

CheckThis is a Fake News Detection website developed by Jonathan Lee as part of the Final Year Project (FYP). The aim of this project is to create a simple web application to help ease the process of verifying the validity of a news article online

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.

Fake News Detection

This is a flask application that detects and identifies the fake or real news.

Sentiment Analysis with Spark Streaming

This webapp helps to find the inaccurate information around the world through news

A project which examines the prevalence of fake news in light of communication breakthroughs made possible by the rise of social networking sites.

Fake News Detection using Scikit-learn

Fake News Detection with Multinomial NB Classifier and Passive Aggressive Classifier

A simple end-to-end project on fake v/s real news detection/classification.

TfidfVectorizer & PassiveAggressiveClassifier

Detecting 'FAKE' news using machine learning.

In this project, with XGBoost and PAC models, it has been tried to guess whether the news is fake or real based on title and content.

NLP program to detect passive aggressive statements

Machine Learning - Binary Classification

Detect Real or Fake News. To build a model to accurately classify a piece of news as REAL or FAKE. Using sklearn, build a TfidfVectorizer on the provided dataset. Then, initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.