In this article we explore if machines can replace us (R programmers) in writing Shiny code. I'll show you some easy applications of a simple model of a recurrent neural network implemented in an R version of Keras
AI will transform the insurance sector. Two techniques that will have the biggest impact are convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The 3rd key to successful AI implementation: productionization
Data scientists must check if the story behind the data makes sense. This requires business knowledge about the data. It's our responsibility to be curious, to explore and challenge to avoid logical problems in the data to save clients money.
CTO Marek Rogala created a convolutional neural network that can recognize certain animals in images. He used state of the art architecture and transfer learning to build a model quickly and with a relatively small dataset.