https://www.acadian-asset.com/investment-insights/owenomics/...
170 karma · joined December 23, 2015
https://www.acadian-asset.com/investment-insights/owenomics/...
I might try and work through the area colleges (St. Mary's, Notre Dame, IU South Bend) if you're looking to recruit there.
I have to wonder, though, why you'd want to go to the movies regularly these days, with all the dreck that Hollywood has been putting out in recent years. Maybe it's time for you guys to hit the $1.99 rentals on YouTube/Amazon/iTunes more often.
The 'Millennials don't like breasts' angle is a new take. I'd figured that one was a constant.
Moreover, executive compensation is still overwhelmingly set via earnings-per-share targets in a fairly transparent manner. If there's a conspiracy afoot to miss targets to benefit an industry sector, the authors haven't identified it.
I like the Matt Levine treatment of this question ('Are Index Funds Communist?'):
https://www.bloomberg.com/view/articles/2016-08-24/are-index...
It's like the fair trade coffee of online bookmarking services.
As for ggplot, the 'grammar of graphics' approach makes it intuitive to get started with but I often run into trouble with both the inheritance hierarchy and with getting graphics 'the last mile' to presentation-quality.
My favorite ggplot2 graphic? The London Cycle Hires Map:
However, it is true that rising education costs are eating much of the ROI of attendance and lack of transparency has made it harder to see where that crossover point is.
But in a world in which the equity and college wage premiums are headed in the directions that they're headed, I would not give this advice to an intelligent 18-year-old.
I've worked around/in data science teams at a large BigCo and I think that you're far overestimating the bar here. There aren't enough people to who can write data pipeline code (SQL/Shell/etc.), much less implement and intelligently explain statistical/ML models. Also, the average decision maker here does not understand the difference between 'created model in Pandas' and 'created model with Amazon's ML API'.
The modal background of data scientists in industry is closer to 'Econ BA + knows Python' than 'Artificial Intelligence PhD'. Moreover, the former will still enjoy a remunerative career if (s)he's sufficiently savvy about identifying problems and showing off how they can be solved with technology.
There may be a point in time when companies can't get a return by throwing math-savvy programmers at a problem, but that will be long after you and I have passed from the scene.
The other way may be the way you use HN. There's a connection between distraction and anxiety/depression; many of us, of course, use HN as a distraction from something else we ought to be doing.
As others have pointed out, there are other ways to learn the material, but it may be that the 'career day' activities, etc. are worth the price of tuition.
http://www.sonicwonders.org/whispering-walls-grand-central-s...