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Fake News Detection Using Recurrent Neural Networks (RNNs) & Long Short Term Memory (LSTM).

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Fake-News-Detection

Currently, we are in a world of mis-information and fake news. The goal is to detect fake news based on Recurrent Neural Networks.

Natural language processors (NLP) work by converting words (text) into numbers. These numbers are then used to train an Al/ML models to make predictions.

Al/ML-based fake news detector is crucial for companies and media to automatically predict whether circulating news is fake or not.

Technology: Data Science | Data Visualization | Tensorflow 2.0 | Fake News Detection | Natural Language Processing (NLP) | Recurrent Neural Networks (RNNs) | Long Short Term Memory (LSTM) | Python | Deep Neural Networks | Artificial Neural Networks | Neural Networks | Deep Learning | Machine Learning | Artificial Intelligence