Linear regression is one of the simplest machine learning algorithms. But also quite useful. It takes a bunch of existing, known observations and tries to predict how new observations will look like. Think about forecasting or finding trends. It says “linear” because the algorithm essentially finds a straight line that most closely follows the observations. OK, let’s take a concrete example. Imagine you are selling your apartment. What is the right price for it? Well, you compare it to similar apartments in your neighborhood. If someone sells the exact same flat across the street, your price should be very similar. If another flat is sold, but 10% larger, expect its price to be 10% higher as well. Yet another flat is half the size of yours. So expect its price to be just 50% of your estimated asking price. Sounds reasonable?
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