In a recent project at STATWORX, I’ve developed a large scale deep learning application for image classification using Keras and Tensorflow. After developing the model, we needed to deploy it in a quite complex pipeline of data acquisition and preparation routines in a cloud environment. We decided to deploy the model on a prediction server that exposes the model through …
Motivation There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics, however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks. At STATWORX we discuss algorithms daily to evaluate their usefulness for a specific project. In any case, understanding these …
Motivation There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics, however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks. At STATWORX we discuss algorithms daily to evaluate their usefulness for a specific project or problem. In any case, …
Introduction Writing appealing interactive web applications – one of STATWORX's many competences – is an ease with R shiny. Just a few lines of code in one R script create the whole logic you need to let the whole magic of shiny happen. It is so simple that you can make a hello world app in a heartbeat, like so. …
Introduction Teaching machines to handle image data is probably one of the most exciting tasks in our daily routine at STATWORX. Computer vision in general is a path to many possibilities some would consider intruiging. Besides learning images, computer vision algorithms also enable machines to learn any kind of video sequenced data. With autonomous driving on the line, learning images …
Everybody talks about them, many people know how to use them, few people understand them: Long Short-Term Memory Neural Networks (LSTM). At STATWORX, with the beginning of the hype around AI and projects with large amounts of data, we also started using this powerful tool to solve business problems. In short, an LSTM is a special type of recurrent neural …
A while back, I started to create an R package that would help me and my collegues at STATWORX with our daily work. After writing the DESCRIPTION file, I did not want to do this ever again. I found the desc package which let's you parse, manipulate and reformat this file via some functions and ergo a script. If you …
In unseren bisherigen Artikeln zu Data Science in Python haben wir uns mit der grundlegenden Syntax, Datenstrukturen, Arrays, der Datenvisualisierung und Manipulation/Selektion auseinander gesetzt. Was jetzt noch für den Einstieg fehlt, ist die Möglichkeit Modelle auf die Daten anzuwenden, um so zum einen Muster in diese zu erkennen und zum anderen Prädiktionen abzuleiten. Die Vielfalt an implementierten Modellen in Python …
As noted elsewhere, sometimes beauty matters. A plot that’s pleasing to the eye will be considered more gladly, and thus might be understood more thoroughly. Also, since we at STATWORX oftentimes need to subsume and communicate our results, we have come to appreciate how a nice plot can upgrade any presentation. So how make a plot look good? How make …
Feature Selection Feature Selection is one of the most interesting fields in machine learning in my opinion. It is a boundary point of two different perspectives on machine learning – performance and inference. From a performance point of view, feature selection is typically used to increase the model performance or to reduce the complexity of the problem in order to …