In this demo users will be able to build neural networks using a drag & drop interface. Different neural network building blocks such as Convolutional, Linear, ReLu, Sigmoid, ... can be configured and connected to form a neural network. These networks can then be connected one of the supported Datasets (i.e. MNIST, CIFAR, ImageNet, ...) to evaluate the network accuracy, visualise the output for specific samples, or train a (small) network (for example in case of MNIST for immediate results). The users can also couple sensors and actuators to a neural network input/output, for example triggering a lamp based on classified camera input. The UI also allows to deploy the neural network building blocks on various different single-board platforms such as Raspberry Pi, Intel Edison and Nvidia Jetson and the difference in response time can be experienced.