+
+ - Add backpropagation algorithm and run a first training round. This is slow, as expected:
+ ```
+ $ time ./train.py
+output vector of first image: [ 0. 52766.88424917 0. 0.
+ 14840.28619491 14164.62850135 0. 7011.882333
+ 0. 46979.62976127]
+classification of first image: 1 with confidence 52766.88424917019; real label 5
+correctly recognized images after initialization: 10.076666666666668%
+round #0 of learning...
+./train.py:18: RuntimeWarning: overflow encountered in exp
+ return 1 / (1 + np.exp(-x))
+correctly recognized images: 14.211666666666666%
+
+real 0m37.927s
+user 1m19.103s
+sys 1m10.169s
+```