Fake_News_Detection

A Machine Learning project designed to detect whether a news article is real or fake based on its text content.

The project uses Natural Language Processing (NLP) techniques to preprocess and transform news articles into numerical features using TF-IDF. Several Machine Learning classification models were implemented and compared, including Logistic Regression, Naive Bayes, Decision Tree, and Support Vector Machine (SVM).

The project also includes an interactive Streamlit application that allows users to enter a news article and receive a real-time prediction.

**Technologies:** Python, Pandas, Scikit-learn, NLP, TF-IDF, SVM, Logistic Regression, Naive Bayes, Decision Tree, Streamlit, Jupyter Notebook, and Google Colab.