Fake_news_detector

Fake news detection system built using TF-IDF vectorization and passive-aggressive classifier, implemented in Python 3.

Libraries used:

1. Numpy
2. Pandas
3. Sklearn
4. Streamlit

▫ TF-IDF : Term Frequency - Inverse Document Frequency Vectorizer is used here to extract a relevant words from the textpool.

▫ PassiveAggressive Classifier : Passive Aggressive Classifier belongs to the category of online learning algorithms in machine learning. It works by responding as passive for correct classifications and responding as aggressive for any miscalculation.

▫ Streamlit : Streamlit is an open source app framework in Python language. It helps us create web apps for data science and machine learning in a short time. Used here to present an attractive UI for the system.