Computational Thinking, Linear Algebra, Linear Regression, Python, Jupyter Notebook.
Let’s start by using the sklearn implementation: regr = linear_model.LinearRegression() %timeit regr.fit(trn, y_trn) 458 µs ± 62.4 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) pred = regr.predict(test) It will be helpful to have some metrics on how good our prediction is. We will look