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Neural Networks
1) The document discusses linear regression and how it can be used to model the relationship between input variables (x) and output variables (y). 2) Linear regression finds the best fitting linear relationship by minimizing the sum of squared errors between the actual y values and the predicted y values from the linear model. 3) The maximum likelihood estimate of the parameters for linear regression can be found in closed form as a function of the input and output data.
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