lesson3.pdf
    lesson4.pdf

    1. import numpy as np
    3. # y = wx + b
    4. def compute_error_for_line_given_points(b, w, points):
    5.     totalError = 0
    6.     for i in range(0, len(points)):
    7.         x = points[i, 0]
    8.         y = points[i, 1]
    9.         totalError += (y - (w * x + b)) ** 2
    10.     return totalError / float(len(points))
    12. def step_gradient(b_current, w_current, points, learningRate):
    13.     b_gradient = 0
    14.     w_gradient = 0
    15.     N = float(len(points))
    16.     for i in range(0, len(points)):
    17.         x = points[i, 0]
    18.         y = points[i, 1]
    19.         b_gradient += -(2/N) * (y - ((w_current * x) + b_current))
    20.         w_gradient += -(2/N) * x * (y - ((w_current * x) + b_current))
    21.     new_b = b_current - (learningRate * b_gradient)
    22.     new_m = w_current - (learningRate * w_gradient)
    23.     return [new_b, new_m]
    25. def gradient_descent_runner(points, starting_b, starting_m, learning_rate, num_iterations):
    26.     b = starting_b
    27.     m = starting_m
    28.     for i in range(num_iterations):
    29.         b, m = step_gradient(b, m, np.array(points), learning_rate)
    30.     return [b, m]
    32. def run():
    33.     points = np.genfromtxt("data.csv", delimiter=",")
    34.     learning_rate = 0.0001
    35.     initial_b = 0 # initial y-intercept guess
    36.     initial_m = 0 # initial slope guess
    37.     num_iterations = 1000
    38.     print("Starting gradient descent at b = {0}, m = {1}, error = {2}"
    39.           .format(initial_b, initial_m,
    40.                   compute_error_for_line_given_points(initial_b, initial_m, points))
    41.           )
    42.     print("Running...")
    43.     [b, m] = gradient_descent_runner(points, initial_b, initial_m, learning_rate, num_iterations)
    44.     print("After {0} iterations b = {1}, m = {2}, error = {3}".
    45.           format(num_iterations, b, m,
    46.                  compute_error_for_line_given_points(b, m, points))
    47.           )
    49. if __name__ == '__main__':
    50.     run()

    data.csv