btc-prices-4.py

def gradient_descent(points, b, m, learning_rate):
    m_gradient = 0
    b_gradient = 0
    
    N = float(len(points))
    for i in range(0, len(points)):
        x = points[i, 0]
        y = points[i, 1]
        
        # Caluclating the partial derivative
        b_gradient += -(2/N) * (y - ((m * x) + b))
        m_gradient += -(2/N) * x * (y - ((m * x) + b))
    
    # Multiplying by learning rate and updating values 
    m_updated = m - (m_gradient * learning_rate)
    b_updated = b - (b_gradient * learning_rate)
    
    return b_updated, m_updated