dbecker

She works at a private institution, and she lists no grants on her CV.

Sure sounds like part of the wake-sleep algorithm, which is impressive given that the wake-sleep algorithm was named in the mid-90s.

I agree that the breadth of high-quality python libraries is great... but in a language that believes

"There should be one-- and preferably only one --obvious way to do it,"

it'd be nice if we weren't also looking for replacements for the standard library.

Out of curiosity: have you done it, or are you just speculating that it isn't difficult?

A quick but possibly meaningless e-mail response doesn't constitute productivity. The expectation you describe is just one of availability (or working), while ignoring productivity or presenting real solutions.

Epidemiology studies can be randomized or observational.

If I looked at the after first, before scanning back and forth, I preferred the after.

Not sure if this is a known cognitive quirk, or even if others would have the same impression.

Your argument isn't any stronger than his would be if he accused you of being selfish for denying your family the opportunity to see more of the world.

I'm witnessing a feeding frenzy for Hadoop talent in situations where there's absolutely no need for Hadoop, and I can't recall anything like this for any other software.

Are you suggesting that most HN readers have easy jobs financed by government largesse?

That strikes me as an absurd suggestion.

Even accepting that this is hyperbole, I think it reflects a disconnect between design aficionados and normal users.

The logos are pretty similar, and I'm skeptical that most people would have a preference either way.

The software part seems manageable, but I've been intimidated by the hardware component.

The presentation may have been inappropriate for this venue, but it's shallow-minded to pretend sexual and sexist are the same thing.

For instance, one could hold a value of relying on evidence rather than preconceived notions.

So, it may be a dream for some enforcement and a nightmare for others.

Maybe you still find deep-learning disappointing, but there have been some successes from having the computer learn multiple levels of internal structure/representation from data.

It is explained in the rest of the comment. I would suggest you read that. For a more in-depth explanation, this also explained in most econometrics textbooks.

Stability of the parameters over time (or over different training sets) is one of the most important properties of a good model.

In some cases it is, in many cases unbiasedness or consistency are more important.

When stability is a priority, collinearity clearly needs to be addressed.

If unbiasedness and/or consistency is a priority, doing nothing is the best option (since removing variables leads to omitted variable bias, PCA does not yield the parameter of interest, and regularization techniques such as ridge regression are both biased and inconsistent).

Leaving all the variables in a regression leads to large standard errors. These large standard errors accurately reflect the uncertainty of having highly related explanatory variables. That is, the data literally can't show which variable is causing the outcome.

Removing covariates leads to smaller standard errors, giving the illusion of certainty.

Obviously, if you are just trying to get p-values less than 0.05, this isn't going to help. Or if you are presenting the data to someone who doesn't understand standard errors, than having standard errors that accurately reflect inferential uncertainty isn't important. And, if the end goal is prediction, this whole point is irrelevant.

But "leave everything in there" is frequently written off when it's the most appropriate approach for representing relationships in the data.

The article claims that has become uncomfortable.

But, as someone who sometimes reads the types of books recommended on this blog post, I've found they have usually been a worse use of my time than writing code.

So, "I don't have time for ___" could be rephrased as "there are better uses of my time than ___." And I think that's a reasonable point of view in this case.

It's easy to fill seats.

The question is whether we have "good enough" software engineers. And, as long as we're trying to improve as a company, we'll always want better engineers.

The fact that Prolog isn't the same as Forth is a complete tangent.

That part is pretty integral to the story.

You might as well say "Take away the part about the pictures and you're just left with a story of a stolen phone."