Optimization Algorithms, Optimization Techniques, Machine Learning, Deep Learning, Convex Optimization.
coefficents # into a polynomial object that can be evaluated p = np.poly1d(np.polyfit(X,Y,1)) print(p) [OUTPUT]: 2.675 x + 2.875 You can see our “hand-calculated” values match very closely the values of slope and intercept obtained using NumPy (the small difference is due to round-off errors in our