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Supervised Learning in Linear Regression by Andi Geng is a document available to read on EtoBox.

What is Supervised Learning in Linear Regression about?

This document discusses supervised learning and linear regression. It introduces supervised learning problems using an example of housing price data. Linear regression is presented as an initial approach to model housing prices as a linear function of features like living area and number of bedrooms. The least mean squares (LMS) algorithm is derived to minimize the mean squared error cost function and learn the parameters of the linear regression model from example data.

Author

Andi Geng

Language

EN