ANN classifier applied on handwritten digits using scikit-learn

An ANN classifier example has been illustrated with the handwritten digits example from the scikit-learn datasets, in which handwritten digits are created from 0 to 9 and their respective 64 features (8 x 8 matrix) of pixel intensities between 0 and 255, as any black and white (or grayscale) image can be represented. In the case of color images, RGB (red, green, and blue) channels will be used to represent all the colors:

# Neural Networks - Classifying hand-written digits  
>>> import pandas as pd 
>>> from sklearn.datasets import load_digits 
>>> from sklearn.cross_validation import train_test_split 
>>> from sklearn.pipeline import Pipeline 
>>> from sklearn.preprocessing import StandardScaler 
 
>>> from sklearn.neural_network import MLPClassifier 
>>> digits = load_digits() 
>>> X = digits.data 
>>> y = digits.target 

# Checking dimensions...