Computational Thinking, Python, Linear Algebra, Math, Mathematics.
5*np.random.rand(100) y = 2*x + 1 + np.random.randn(100) x = x.reshape(100, 1) y = y.reshape(100, 1) X = np.hstack([x, y]) X.shape (100, 2) Let’s plot the data: plt.plot(X[:,0], X[:,1], '*') plt.show() Highly correlated data means that the dimensions are redundant. It is possible to predict one