# Start matplotlib inline mode, so figures will appear in the notebook
%matplotlib inline

# Import the example plot from the figures directory
from figures import plot_sgd_separator
plot_sgd_separator()

%load figures/sgd_separator.py



from figures import plot_linear_regression
plot_linear_regression()

%matplotlib inline
import numpy as np
from matplotlib import pyplot as plt

from sklearn import datasets
digits = datasets.load_digits()

digits.data

digits.target

digits.images[0]

from sklearn import svm
clf = svm.SVC(gamma=0.001, C=100.)

clf.fit(digits.data[:-1], digits.target[:-1])

clf.predict(digits.data[-1])

plt.figure(figsize=(2, 2))
plt.imshow(digits.images[-1], interpolation='nearest', cmap=plt.cm.binary)

print(digits.target[-1])