When being the first in your company to apply a deep learning algorithm on your data you often have to overcome several obstacles. One challenge is to understand your data and to form a training and test dataset. Another one is to get your algorithms and its performance accepted and integrated in your existing processing workflow.
Convolutional Neural Networks have become a standard tool in processing image data. They have shown to reach human-level classification performance on some object recognition tasks.
In this talk I will present my experiences in getting started using a convolutional neural network for classification of 2D sensor data. I will point out the importance of understanding your data and give hints of how to select your train and test datasets according to the requirements. Furthermore, I will show how to get a feature extractor out of the classifier and how to visualize it.