In this project, I built a system to identify and classify fake news articles using Python and MySQL. The project involved collecting news data and storing it in a MySQL database for efficient access and management. Natural Language Processing (NLP) techniques were applied to clean and process the text data, preparing it for model training.

• Languages & Tools: Python, MySQL, Pandas, Scikit-learn, NLTK
• ML Algorithms: Logistic Regression, Naïve Bayes
• Features: Text preprocessing (stopword removal, stemming), TF-IDF vectorization, model evaluation, database integration

• Detects fake vs. real news using machine learning techniques
• Applies NLP methods for efficient text data processing
• Trains models using labeled datasets to improve accuracy
• Uses MySQL to store and retrieve news data reliably

The system achieved reliable accuracy in detecting fake news articles and demonstrated the practical importance of merging machine learning with database systems to combat misinformation effectively.