#Generate Toy Dataset
import pylab
import numpy
x = numpy.linspace(-1,1,100)
signal = 2 + x + 2 * x * x
noise = numpy.random.normal(0, 0.1, 100)
y = signal + noise
pylab.plot(signal,'b');
pylab.plot(y,'g')
pylab.plot(noise, 'r')
pylab.xlabel("x")
pylab.ylabel("y")
pylab.legend(["Without Noise", "With Noise", "Noise"], loc = 2)
x_train = x[0:80]
y_train = y[0:80]
# Model with degree 1
pylab.figure()
degree = 2
X_train = numpy.column_stack([numpy.power(x_train,i) for i in xrange(0,degree)])
https://pastebin.com/6SjnevJS