Building an optical character recognizer using neural networks

Now that we know how to interact with the data, let's build a neural network-based optical character-recognition system.

How to do it…

1. Create a new Python file, and import the following packages:

   import numpy as np
   import neurolab as nl

2. Define the input filename:

   # Input file
   input_file = 'letter.data'

3. When we work with neural networks that deal with large amounts of data, it takes a lot of time to train. To demonstrate how to build this system, we will take only 20 datapoints:

   # Number of datapoints to load from the input file
   num_datapoints = 20

4. If you look at the data, you will see that there are seven distinct characters in the first 20 lines. Let's define them:

   # Distinct characters
   orig_labels = 'omandig'
   
   # Number of distinct characters
   num_output = len(orig_labels)

5. We will use 90% of the data for training and remaining 10% for testing. Define the training and testing parameters:

   # Training and...