A couple of years ago I saw a TED-talk on AI and the first pieces of art created with a neural network and I thought to myself "Wow! This is so cool!". My first passion growing up was drawing and I had a bizarre taste in pictures....they resembled quite a lot what is shown in... 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 →
A gentle introduction to Image Recognition by Convolutional Neural Network
When people hear the words "Artificial intelligence" they most often tnink of either robots or automated system with the ability to distinguish between objects. The latter is what in the area of analytics knows as image recognition, a specific branch of a much wider set of techniques known as Deep Learning. When curious minds undertake... Continue Reading →
A health-care inspired random forest model: Predicting risk of heart failure
In my previous blog post, Random Forest: An intuitive and an analytical introduction (part 1: Decision trees), I discussed the theory behind decision trees and was deliberately technical because I believe that understanding the methods used is a key to making good predictions. It is however not enough to have a theoretical knowledge of a particular... Continue Reading →
24 hour predictions of PM10 levels in urban environments
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