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What is Linear Regression in Machine Learning about?

This document provides an overview of linear regression models and techniques. It introduces linear regression, discusses how to fit linear models to data by minimizing loss functions like squared error, and describes methods like regularized least squares and the lasso that add regularization terms to the loss function to prevent overfitting. It also covers concepts like the bias-variance tradeoff and online learning using stochastic gradient descent.

Author

Deepa Devaraj

Language

EN