Machine Learning

Running Tensorflow with native Linux Binaries in the Windows Subsystem for Linux

After 4 hours of unsuccessful attempts to set up tensorflow in Docker on Windows, I decided to – just for fun – try to run it in the shiny new Windows Subsystem for Linux on my Windows 10 Insider Preview Build 14332. What began with low expectations turned out to be very successful, so here are the steps: First enable the Windows Subsystem for Linux in the “Turn Windows features on or off” dialog: Then open the Ubuntu Bash and update the package index: You can now proceed to install pip for Python 2: Now install the CPU-enabled Linux x64 tensorflow package:: Tensorflow is now installed. With the following command, you can get the directory of the installed package: This should give something like “/usr/local/lib/python2.7/dist-packages/tensorflow”. Now let’s cd to the directory with the example implementation of a CNN for the MNIST dataset: And run the convolutional neural network: In the…

C#

Learn and Predict the Gender of German Nouns

The German language is know to be relatively complicated and especially the gender causes lots of confusion. While English has only one article (the), three different articles are used in German: der (male) die (female) das (neuter) While rules to determine the gender of a noun exist, almost no German native speaker can name them. We can now solve this problem (determine the gender without memorizing the rules) using some simple machine learning with the Accord framework. Let’s quickly name the steps that will follow: find and extract a dataset of noun-gender associations split into training, test and validation dataset extract features into something the algorithm can use train a Naive Bayes test the model with the test dataset After quite a while of searching, I found this machine readable and CC-BY-SA 4.0 licensed XML file from Daniel Naber. In our Universal Windows App we can then load all nouns into…

Uncategorized

iGEM Aachen 2014

You might have wondered why it got a bit more quiet on my blog. Now here’s why: Because of the iGEM competition 2014. The iGEM competition is an international competition in synthetic biology that debuted at MIT in 2004. Since then it has grown to more than 230 participating teams from all over the world. Over the last ten years it has significantly shaped the international synthetic biology community. In 2013 a few friends and me heard of the competition and founded the first team from RWTH Aachen. Up until March 2014 our team grew to 15 students of Bachelor and Master programs in Biology, Biotechnology, Biomedical Engineering, Computational Engineering Science and Computer science. After almost a year of hard work, we finished our project “Cellock Holmes – A Case of Identity” and flew to the Giant Jamboree (Finals) in Boston, MS, We had fulfilled all criteria for the gold medal…