Build data for the "CMAPSS" examples from the NASA C-MAPSS (Commercial Modular
Aero-Propulsion System Simulation) Aircraft Engine dataset. This contains
engine sensor data over time until the engine reaches failure. The original
dataset and more information can be found on the NASA Intelligent Systems
Division website:
https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/#turbofan

There are two examples using this dataset. One example uses a feed forward
neural network (CMAPSS_NN/) and the other reshapes the data in preprocessing so
that a convolutional neural network can be used (CMAPSS_CNN/). These examples
demonstrate how to train models that predict a continuous dependent variable.

In the preprocess script the RUL values are calculated for every sample of data
in the train and test sets. The "id" and "cycle" columns are dropped, the data
is scaled and for the CNN model the data is segmented into 24 X 30 windows of
data to be processed by the convolutional layers.
