Detect Fake News with Machine Learning & Feature Engineering

Learn how to build fake news detection model using machine learning, feature engineering, logistic regression, and NLP

Created by: Christ Raharja
Ex Technology Risk Consultant, and E-commerce enthusiast

What Will I Learn?

• Learn how to build fake news detection model with feature engineering
• Learn how to build fake news detection model with logistic regression
• Learn how to build fake news detection model with Random Forest
• Case study: applying feature engineering to predict if a news title is real or fake
• Learn the basic fundamentals of fake news detection model
• Learn factors that contribute to the widespread of fake news & misinformation
• Learn how to perform news source credibility
• Learn how to detect keywords associated with fake news
• Learn how to perform news title and length analysis
• Learn how to detect sensationalism in fake news
• Learn how to detect emotion in fake new with NLP
• Learn how to evaluate fake news detection model with confusion matrix
• Learn how to perform fairness audit with demographic parity difference
• Learn how to mitigate potential bias in fake news detection
• Learn how to clean dataset by removing missing rows and duplicate values
• Learn how to find and download datasets from Kaggle

Requirements

• No previous experience in machine learning is required
• Basic knowledge in Python and statistics

Target audience

• People who are interested in building fake news detection system using feature engineering, logistic regression, and machine learning
• People who are interested in detecting emotion and and sensationalism in fake news using NLP