Linear Regression is an old school statistical method for predicting outcomes from a series of numbers. It uses some intermediate math to automatically find patterns in data – like historical stock prices – and create a formula for what the expected output might be (stock price) given a new input (date and time). Though less in vogue these days, Linear Regression was highly popular and effective for traditional Machine Learning tasks before GenAI came around.