Building an Optical Character Recognition engine

Now that we have learned how to work with this data, let's build an optical character recognition system using artificial neural networks.

Create a new python file and import the following packages:

import numpy as np 
import neurolab as nl 

Define the input file:

# Define the input file 
input_file = 'letter.data' 

Define the number of datapoints that will be loaded:

# Define the number of datapoints to  
# be loaded from the input file 
num_datapoints = 50 

Define the string containing all the distinct characters:

# String containing all the distinct characters 
orig_labels = 'omandig' 

Extract the number of distinct classes:

# Compute the number of distinct characters 
num_orig_labels = len(orig_labels) 

Define the train and test split. We will use 90% for training and 10% for testing:

# Define the training and testing parameters 
num_train = int(0.9 * num_datapoints) 
num_test = num_datapoints - num_train 

Define...