Stochastic Gradient Descent

sgd.py

from random import random, seed
from datetime import datetime


seed(datetime.utcnow().microsecond)


def main():
    X = list(range(0, 25))
    Y = [*map(lambda x: 2.0 * x + 3, X)]

    weight = {
        'w0' : random(),
        'w1' : random(),
    }

    lr = 0.05

    for epoch in range(1000):
        for x,y in zip(X, Y):
            y_prime = weight['w0'] + (x * weight['w1'])
            weight['w0'] -= lr * 2.0 * (y_prime - y) / len(X)
            weight['w1'] -= lr * 2.0 * (y_prime - y) * x / len(X)
        print(weight)


if __name__ == '__main__':
    main()