Go gaga over Machine Learning

Here are a few interesting visualizations that I found while doing research for my talk about testing Insights, also included are the ones that I did not end up using: Open source contributions by location  http://davidfischer.github.io/gdc2/#languages/All GitHut - is an attempt to visualize and explore the complexity of the universe of programming languages used across the repositories hosted on GitHub. http://githut.info/ Who speaks what on GitHub? Visualization 1 is a chord diagram, which indicates the relationship between all possible combinations of programming languages. This data was computed by creating all possible pairs that could be created using the list of 20 languages I have analyzed. By analyzing the combinations, and the number of users that speak both of the languages in question, we get a good idea of what languages are spoken most, but also which languages are 'spoken' quite a lot, but not in combination. It gives a different perspective of th

Here is the link to my talk at Tconf :

Some of us here are working on the BDD guidelines that should be followed: Would be interested to hear if anyone has thoughts to share: Guidelines Explain in the feature file what the feature is about, just after the “Feature: ” before proceeding to the scenarios (preferably in “In order/As a/I want” format). Write high-level scenario steps by raising the level of abstraction and focus on the “what” rather than the “how” don’t mention UI elements don’t mention ‘click’ or other actions linked to specific UI elements the scenario should remain valid if the UI is replaced with a new UI tomorrow avoid very detailed steps where possible (helps to focus and avoid clutter) Write scenarios using business language rather than using technical language so that it can be understood by everyone. Write scenarios from the perspective of the person who will use or needs the feature (not always a member or user). Use 'I' and explain who the 'I' is in 'Given' s