Linear Regression with Gradient Descent + Least Squares

Linear regression is a powerful statistical tool for data analysis and machine learning. It assumes a hypothesis (model) that is a linear combination of the independent variables. Using gradient descent, the parameters of the model can be learned using the available data; both the batch gradient descent and stochastic gradient descent algorithms are detailed here. Another way of looking at linear regression is through linear least squares, we also explore that solution.

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