fake news detector
using BERT & transfer learning
During my 5 week fellowship at Data Science for All Women’s Summit (Fall 2020), my teammates and I built a fake news detector using various natural language processing tools such as embeddings, RNN, BERT, and transfer learning. We performed careful preprocessing to remove biases in the dataset, and we used a model interpretability tool called LIME to identify points of improvement for our model.
Take a look at our code on GitHub!