https://github.com/gtraines/linear-regression

Linear regression is an approach to machine/statistical learning generally applied to value prediction problems. It is a form of supervised learning, wherein the training data provides the “correct” answer in addition to the data points generated by an unknown function, (*f*). Although in this case we were provided a 2-dimensional data set, linear regression can be used on higher-dimensional data sets. The linear regression method assumes that the unknown function *f *can be approximated using a polynomial linear equation of *d *terms (the number of features being measured plus a constant value for bias). Among machine learning algorithms, it is fairly simple, and in his CalTech lectures Dr. Abu-Mostafa calls linear regression “one-step learning.”

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## always choosing the local optimum