Computational Thinking, Python, Linear Algebra, Linear Regression, Jupyter Notebook.
name2func[name] t = timeit.timeit(fcn + '(A,b)', number=5, globals=globals()) df.set_value(name, (m,n), t) coeffs = locals()[fcn](A, b) reg_met = regr_metrics(b, A @ coeffs) df_error.set_value(name, (m,n), reg_met[0]) df df_error store = pd.HDFStore('least_squares_results.h5') store['df'] = df