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 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 data points 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...