compactmani

This is a nice project. I think it would be great to add references used for the implementations and some tests that demonstrate they return what is expected (or perhaps the same result of sklearn maybe).

I think it's the best part. The definition is left for the student to learn.

Their data scientists will now be building features like "tried to watch a movie from a VPN IP" for their churn models.

And another note: there are also people who simply do not allow comcast to filter their traffic and therefore always have a VPN. These people despite their efforts to watch netflix content approved for their own country, would be blocked.

I tried it with my favorite, Alex Webb. It didn't break 5/10 and received solid #mess and #boring tags on all of the photos. Fun none the less.

The main finding from my perspective is that we can score and rank friendship likeliness and see signal in a hold out dataset.

I can almost hear Facebook clamoring to offer free genotyping.

I see the optimization problem they face. Promote non-personal content to generate short term revenue versus promote personal content to minimize long-term churn. It looks like their data scientists and business analysts have identified significant risk to pursuing the former and advocate the latter, for now.

In other words this has nothing to do with a return to claimed core values, but a shift in strategy to remain afloat for as long as possible.

That's also the base salary. Yearly bonus can easily be 100% of the salary. Partners at decent firms are of course clocking ~2M or more.

Can you give some concrete examples of the benefits of wrangling in python over R and a general sense of how much time this would save a user?

This is consistent with my impression of how sales work. You sell a feature, product, capability, etc that won't be ready for at least 6 months (for example). Then you kindly encourage an engineer to build it.

I agree. The title should read 'Where Can a Ph.D. Take You? Forward to More Research, Usually'

Which is the entire point getting a PhD in the first place. More research. Forever.

I (along with many others) cringed at the phrasing of postdoctoral degree. A post-doc is not a degree. The article's comparison of a post-doc to law school for liberal arts majors was equally egregious. Sloppy writing.

Now, to be fair to their point. What they are observing is a cultural phenomenon in academia which is to stay in academia until you can't stay any more. Industry is for those who fail at academic research, whether that failure occurs at the post-doc stage or pre-tenure stage. This is in contrast to the sentiments of the real world (the perspective of the article author) which wonders why these "students" take so long to get a real job.

Allow me to make a more general conjecture: As an online discussion grows longer, the probability of a comparison involving word_x or word_y approaches 1.

I think it's more like: made a decision about god? if yes and believe there is one then theist else if believe there isn't one then atheist.

A lot of people I think don't care to form a belief one way or another. I'm not sure what that's called.

You've highlighted one of the many advantages to browsing with javascript off by default. I think at this point it should really only be used for must-have cases.

This is a project developed by a high school senior. Yes he made rookie choices as have been pointed out here. If you like the direction of the project, contribute! It will help him learn.

600 million PC users discovered that running a lightweight unix distribution/DE and not allowing javascript made the life expectancy of their computers triple.

Or so I dream.