There are typically three tasks that neural networks does:

• Import data
• Recognize the patterns of the data by training 
• Predicting the outcomes of new data

Neural networks take in data, trains themselves to recognize the patterns of the data, and then are used to predict the outcomes of new data. This recipe uses the cleaned and feature engineered dataset saved in the previous recipe. The X_train dataset is pulled in from the spark data table into a Panda DataFrame. The training DataFrames, X_train, and y_train are used for training. X_test gives us a list of devices that have failed and y_test gives us the real-time failure of those machines. Those datasets are used to train models and test the results.

First, we have the input layer. The data is fed to each of our 32 input neurons. The neurons are connected through channels. The channel is assigned a numerical value known as weight. The inputs are multiplied by the corresponding...