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Python: Real World Machine Learning
book

Python: Real World Machine Learning

by Prateek Joshi, John Hearty, Bastiaan Sjardin, Luca Massaron, Alberto Boschetti
November 2016
Beginner to intermediate
941 pages
21h 55m
English
Packt Publishing
Content preview from Python: Real World Machine Learning

Building a single layer neural network

Now that we know how to create a perceptron, let's create a single layer neural network. A single layer neural network consists of multiple neurons in a single layer. Overall, we will have an input layer, a hidden layer, and an output layer.

How to do it…

  1. Create a new Python file, and import the following packages:
    import numpy as np
    import matplotlib.pyplot as plt
    import neurolab as nl 
  2. We will use the data in the data_single_layer.txt file. Let's load this:
    # Define input data
    input_file = 'data_single_layer.txt'
    input_text = np.loadtxt(input_file)
    data = input_text[:, 0:2]
    labels = input_text[:, 2:]
  3. Let's plot the input data:
    # Plot input data plt.figure() plt.scatter(data[:,0], data[:,1]) plt.xlabel('X-axis') ...
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Publisher Resources

ISBN: 9781787123212Supplemental ContentPurchase Link