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...