ashharr / detecting-fake-news-classifier

To build a model to accurately classify a piece of news as REAL or FAKE. The detection of fake news is done from saving oneselves from believing in false information. All the news that are read on social media cannot be trusted or relied upon. Hence the aim of our project is to detect such fake news by using tf-idf vectorization on news data sets, calculating the confusion matrix of our model and generating its accuracy for prediction of fake news. Using sklearn, we build a Tf-Idf Vectorizer 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.

Hey, I'm Ashhar!

I am Ashhar Shaikh, a Computer Engineering graduate and a Software engineer with two years of development experience.

Talking about Personal Stuffs:

• 👨🏽‍💻 I’m currently working on ticktrack;
• 🌱 I’m currently learning Spring Boot and React;
• 👯 I’m looking to collaborate on ticktrack 🤝;
• 🤔 I’m also looking for help with Data Structures and Algorithms;
• 💬 Ask me about anything, I am happy to help;
• ⚡️ Fun-Fact: I won the India's largest hackathon SIH in 2019 for buidling ML Chatbot
• 📫 How to reach me: [email protected];
• 📝Resume && Portfolio

Languages and Tools:

⭐️ From ashharr