How a Straight Line Teaches Machines to Learn

The article delves into the fundamentals of linear regression and its connection to machine learning, illustrating how concepts like slope and intercept form the basis for making predictions. By using house pricing as an analogy, it emphasizes how linear regression models can estimate values by fitting a best-line through data points. The piece also discusses error measurement, explaining how the least squares method helps determine the best fitting line, and introduces gradient descent as a technique to refine predictions further.

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