I wrote a little wrap-up of this year’s Google Summer of Code Mentor Summit over on the 52° North Blog.
This is the most funny thing you will read this weekend:
The plan: get a robot arm, have it pour cereal and milk into a bowl and feed it to me with a spoon. The only catch was that I had to learn how to program a robot arm and code a pretty complicated sequence to have it serve me breakfast. But I was up for the challenge, because the best way to avoid real problems is to deal with fake ones.
The US Census provides an incredible wealth of data but it’s not always easy to work with it. In the past, working with the tabular and spatial census data generally meant downloading a table from FactFinder and a shapefile from the boundary files site and joining the two, perhaps in a GIS system. These files could also be handled in R but getting the data, reading it into R and, in particular, merging tabular and spatial data can be a chore. Working with slots and all the different classes of data and functions can be challenging.
A recent interesting post on stackoverflow by Claire Salloum prompted me to revisit this issue in R and I’ve definitely found some valuable new packages for capturing and manipulating Census data in R.
Great post explaining how to wrangle and map census data in R.
Google Summer of Code 2015 is coming to an end today. I’ve been mentoring Deepak over the summer, who built an awesome prototype to bring the enviroCar data into the LOD cloud.
If you were always wondering how machine learning works, but didn’t dare to ask.
This protection is important for everyone. It’s easy to see how encryption protects journalists, human rights defenders, and political activists in authoritarian countries. But encryption protects the rest of us as well. It protects our data from criminals. It protects it from competitors, neighbors, and family members. It protects it from malicious attackers, and it protects it from accidents.