Understanding Linear Regression and Its Applications

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This overview covers the fundamentals of linear regression, including the equation y = mx + c, the significance of slope and intercept, and practical applications using house size and price. It also delves into cost functions, focusing on minimising squared errors and employing gradient descent to find the global minimum, with an extension to multiple independent features.