Today, we live in a world of mis-information and fake news. The goal of this project is to detect fake news based on Deep Learning Model (Long Short Term Memory). I will use Natural Language Processors (NLP) by converting words (text) into numbers. These numbers are going to be used to train our models to make predictions. Fake news detector is crucial for companies and media to automatically predict whether circulating news is fake or not. I will analyze thousands of news text to detect if it is fake or not.
Datasets can be downloaded from here .
I built a LSTM classifier model by acquiring 0.997 accuracy score that means our model predicted almost all of them accurately. I saved the best model and we can use it for further classifier projects by loading model. We have 25 false classified news out of total 44898 news according to confusion matrix.