Peekaboo

Last week I was at Pycon DE , the German Python conference. After hacking on scikit-learn a lot last week, I decided to to something different on my way back, that I had planned for quite a while: doing a wordl -like word cloud . I know, word clouds are a bit out of style but I kind of like them any way. My motivation to think about word clouds was that I thought these could be combined with topic-models to give somewhat more interesting visualizations. So I looked around to find a nice open-source implementation of word-clouds ... only to find none. (This has been a while, maybe it has changed since). While I was bored in the train last week, I came up with this code . A little today-themed taste:

Recently I entered my first kaggle competition - for those who don't know it, it is a site running machine learning competitions. A data set and time frame is provided and the best submission gets a money prize, often something between 5000$ and 50000$. I found the approach quite interesting and could definitely use a new laptop, so I entered Detecting Insults in Social Commentary. My weapon of choice was Python with scikit-learn - for those who haven't read my blog before: I am one of the core devs of the project and never shut up about it.