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def gradient_descent(training_examples, alpha=0.01):
    """
    Apply gradient descent on the training examples to learn a line that fits through the examples
    :param examples: set of all examples in (x,y) format
    :param alpha = learning rate
    :return:
    """
    # initialize w0 and w1 to some small value, here just using 0 for simplicity
    w0 = 0
    w1 = 0

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def multivariate_gradient_descent(training_examples, alpha=0.01):
    """
    Apply gradient descent on the training examples to learn a line that fits through the examples
    :param examples: set of all examples in (x,y) format
    :param alpha = learning rate
    :return:
    """
    # initialize the weight and x_vectors
    W = [0 for index in range(0, len(training_examples[0][0]))]

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