The company blog of Yhat, a data science software firm, with tutorials on R, Python, SQL, ggplot, and its Rodeo IDE.
HN commenters mostly mention it for Rodeo, which one user calls a fairly robust integrated analysis environment, like a more immediate Jupyter notebook.
Every event is truly massive. It's made worse by the fact that it's an entirely preventable problem. Surely the problem is that at the moment there's so many that car companies don't even count the minus-one points. It's minus 33,000 points per year in the US alone. [1]
What worries me is that we're dreaming up massive fear scenarios. I see the aim of the automation is to prevent the scenarios from ever happening. Sensible speeds with sensible distances.
We can never make it to having zero casualties unless we can first get to a stage where we can treat accidents as an abnormality. Something that needs to be investigated in the same manner as an aircraft crash.
I too hate terms like "acceptable losses" as well as it brings up the truly horrible "cost-benefit" analysis that Ford did [2] with it being cheaper to pay out to the dead relatives rather than fix the problem. I too worry that if we accept lower standards for software now, it will set a precendent with 'acceptable' deaths that will only get lowered.
If Tesla can apply the level of analysis that approaches airplane crash investigation as well as fixes to prevent each death - then I believe we're on the best path.
It's also worth noting that Tesla used the word 'crash' rather than 'accident' in this report, something which has been highlighted [3] as another thing we can do to improve investigations into road deaths.
[1]: http://blog.yhat.com/posts/traffic-fatalities-in-us.html
[2]:…
It seems like this list is incomplete without mentioning that both RStudio[1] and Jupyter[2] notebooks now have really first class support for R. There are also two upstatrs, Rodeo[3] and Beaker[4] are doing cool stuff as well.
The company I work for, Domino Data Lab[5], let's you fire up a lot of these notebooks in a nice hosted environment on big cloud servers with minimal cost and effort. It's a fun way to learn how all these new environments can work together. From RStudio for exploratory analysis, to Jupyter notebooks for presenting a topic. The other two I haven't really found the superior use-case. The tools in this space are just getting better and better.
1. https://www.rstudio.com/
2. http://jupyter.org/
3. http://blog.yhat.com/posts/introducing-rodeo.html
4. http://beakernotebook.com/
5. https://www.dominodatalab.com/
Since the comment from the new account mentioning it may be modded away, I'll say (as a recent user, not affiliated with them in any way) that Rodeo is a fairly robust integrated analysis environment, a more immediate kind of Jupyter notebook. They recently added a native dataframe viz, too.
http://blog.yhat.com/posts/rodeo-2.0.6-dataframes.html
How does this differ from Rodeo [1]?
[1] http://blog.yhat.com/posts/introducing-rodeo.html
Rodeo is a good start:
http://blog.yhat.com/posts/rodeo-native.html
http://blog.yhat.com/: Tutorials, example apps, and other stuff.