You want to predict yes or no. Spam or not spam. Sick or healthy. Fraud or legit. That's a classification problem. And despite its confusing name, logistic regression is one of the best tools for it. It doesn't predict a number. It predicts a probability. Then it uses that probability to make a yes or no decision. Simple idea. Powerful in practice. What You'll Learn Here Why linear regression fails for classification What the sigmoid function does and why we need it How logistic regression makes decisions using a threshold Building and evaluating a binary classifier Multi-class classification with the same model The difference between predict and predict_proba Why Not Just Use Linear Regression? You might think: house prices were numbers, exam scores were numbers, so just use linear regression and predict 0 or 1. The problem is linear regression can predict values outside 0 and 1. It might predict 1.8 or -0.3. Those don't make sense as probabilities. Also, a straight line is a bad fit for binary data.…