Keras Deep Learning Cookbook

How to do it…

1. Next, let's define the parameters to be used in our simple network, as well as the DataFrame where we are going to store the results, as follows:

n_lag = 1n_repeats = 30n_epochs = 1000n_batch = 4n_neurons = 3results = DataFrame()

2. We then call the experiment method as follows:

results['results'] = experiment(series, n_lag, n_repeats, n_epochs, n_batch, n_neurons)

Inside the experiment() method, we are processing the data through the network as follows:

def experiment(series, n_lag, n_repeats, n_epochs, n_batch, n_neurons):  # method details ....

3. First, we get values of the series DataFrame, as follows:

raw_values = series.valuesdiff_values = difference(raw_values, 1)

The output of raw_values and diff values is as follows: ...