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Linear Regression is a supervised learning algorithm used for predicting a continuous dependent variable (Y) based on independent variable (s) (X). The hypothesis function is: ...

Learn how to estimate linear regression model parameters in machine learning using ordinary least squares and gradient descent. Compare their advantages and disadvantages.

given a training set of N (xi, yi) pairs, the goal is to learn the hw that best fits the training data; this is called linear regression traditionally, linear regression tries to minimize this ...