The funnel shape of the scatter plot immediately reminded me of an article on the insensitivity to sample size pitfall [0], which points out that you'll expect entities with smaller sample sizes to show up more often in the extremes because of the higher variance.
Looks like the tags with the biggest differences exemplify this pretty well.
There seems to be a pretty wide spectrum of abstraction for DL tools, from writing by hand to Theano to Keras, for example. Will this course focus on any tool in particular?
I often find myself frustrated when an important decision is made with little explanation in politics or business by someone who I assume is intelligent. It may strike me as a bad decision, but I try to be charitable and assume they have a good reason. I've thought that they often don't offer good explanations because they feel too busy to take the time to communicate, they're just not good at communicating or they don't recognize its importance.
This post suggests they could also have a better perception of the possible risks that even effective communication could entail than I do.
My wife and I have done some of the same coursework (for different degrees), me on campus and hers online. I actually would have preferred online. Rigor seemed equivalent, but I find the ability to pause and rewind lectures invaluable.
I occasionally use probabilistic programming systems, and find this project fascinating, but I've been wondering for a while what the vision is.
Is it meant mainly as a research project/proof of concept (seems I've seen elsewhere that it's funded by the DARPA PPAML project), or is it intended to become a commonly used piece of software with a community like pymc3 and stan?
This seems intuitive. Scott Adams expresses a similar idea as focussing on 'systems' rather than 'goals.' Failing to meet a goal leaves you with nothing if the goal is all you focus on, but what you learn from the system is more reusable.
I have no idea about Zeppelin's lineage, but looks like there's also Spark Notebook https://github.com/andypetrella/spark-notebook which more closely resembles the IPython notebook. I'd love to hear an explanation of the differences between all of these notebooks.
Can't wait to see if the Jupyter split will contribute to a consolidation or proliferation in the notebook-verse...
The 'guilt and control' phenomenon also looks like it shows up in deciding whether to leave your children at home during a quick trip out. While a road accident may be much more likely than an accident alone at home, good luck explaining that to either the parents or the law. The desire to feel in control frequently seems to be very hard to reason against.
Have you found a good framework that purescript supports in the vein of Angular or React? I had a look a while back but the support was a bit spotty for me.
My perception is that the FDA's on the hook if they promote a drug that turns out not so safe/effective, and CDC's on the hook proportional to how much damage the flu wreaks. In which case I'd expect the FDA to be extremely conservative about promoting it, and the CDC to push anything with even a marginal effect, no matter other costs.
Looks like the tags with the biggest differences exemplify this pretty well.
[0]- http://dataremixed.com/2015/01/avoiding-data-pitfalls-part-2...