When AI goes Peltarion

A while ago, I wrote a blog post on convolutional networks (A gentle introduction to Image Recognition by Convolutional Neural Network) in which I described the mathematics and inner workings of these networks. To write the post I created a model to classify "birds" and "airplanes" from a training set containing a total of 8000 images... Continue Reading →

DICOM, A useful and secure medical data format and an introduction to non-medical learning pathology detection using Convolution Neural Networks

Important note to the reader This blog can be seen as both a description of a particular R-package, oro.dicom, which is widely used in medical research in which imaging and patient information is used and as an introductory post to a future blog on pathology detection using convolutional neural networks. As many who read my... Continue Reading →

Visualization of data with maps

As a child I spent hours looking at atlases and desk globes. I was fascinated and dreamt myself away to all corners of the world....and I have today travelled and lived in most of the places I was dreaming of. Today, as an analyst, I enjoy combining data about different countries and I have found... Continue Reading →

The customer is always right….

....a brute force method to analyze customer reviews Two travellers headed for the same final destination but booked on different flights, one is satisfied and the other can't stop swearing about the service and that the airline couldn't do it's job properly. Who hasn't heard this one before? This could of course be isolated unfortunate... Continue Reading →

Estimation through simulation

I recently came across a question from one of my retail clients that I took great pleasure in solving. It was interesting to me both because of the clear usefulness of retrieving the answer for my client and also for the brainteasing nature of the problem. In this post I’m going to share both the... Continue Reading →

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