Demystifying Machine Learning: How Logistic Regression Enables Clear Binary Predictions
• Explains logistic regression is optimal for binary classification problems, translating numerical data into binary outcomes
• Logistic regression calculates the probability of an event occurring, measuring the likelihood something belongs to a certain class
• Uses a sigmoid function to convert logistic regression's linear output to a 0-1 probability
• Allows clear decision-making from data when there are two distinct, categorical options
• Breaks down machine learning concepts to their basics, starting with simple building blocks like logistic regression