Python Machine Learning Cookbook - Second Edition

How to do it...

Let's see how to build a recurrent neural network for sequential data analysis:

1. Create a new Python file, and import the following packages (the full code is given in the recurrent_network.py file that is provided to you):

import numpy as np 
import matplotlib.pyplot as plt 
import neurolab as nl 

2. Define a function to create a waveform, based on input parameters:

def create_waveform(num_points): 
    # Create train samples 
    data1 = 1 * np.cos(np.arange(0, num_points)) 
    data2 = 2 * np.cos(np.arange(0, num_points)) 
    data3 = 3 * np.cos(np.arange(0, num_points)) 
    data4 = 4 * np.cos(np.arange(0, num_points)) 

3. Create different amplitudes for each interval to create a random waveform:

 # Create varying amplitudes amp1 = np.ones(num_points) ...