I must be missing something, I buy Bitcoin with a USD bank account, I send to another address and then this address sends to a known drug dealer. How do they establish the second address's identity?
It reads like no one had any sense of how well they would do on the test. So people guessed they'd be slightly above average which is a good prior for a group of Ivy league students. This lead to the lowest being "overconfident" and the best being "under confident". Designing good studies is hard.
SWE did good work, got passed over for promotion several times, got mad and quits cushy software job to freelance. Everyone sympathizes because everyone thinks they do promotion-worthy work.
I'm actually not surprised that journalists overestimated Hillary's chance of winning. As a group, they are predominantly coastal and almost uniformly college educated. Both of those groups broke disproportionately toward Hillary.
Non-college educated Americans broke disproportionately toward Trump. It would seem given the relationship between college graduation and cognitive ability (the bottom 20% in cognitive ability rarely graduates from college) that this is reasonable support for the correlation of fake news belief with Trump support.
The real issue is that the converse statement is rarely true. Providing less value to your customers is a way to be paid more. Obviously as the entire thread points out, the outcomes are probabilistic in nature and certain job titles have low ceilings on wages as do certain companies.
As a barber, you can only cut one person's hair at a time. Regardless of your customer service, this will limit your impact and compensation. Own a chain of barbershop and you'll impact more people and be compensated accordingly.
This thread seems to dedicated to the annoying cap on individual contribution in a team game.
This is like describing a painting to a blind person. Describing "a dust-covered sunflower" as a "yellow flower" doesn't much help the blind person and certainly doesn't help the sighted.
The simple answer is that this blog post tells us nothing about her skill level aside from the clear resume brags. Google I/O presenter on Tensorflow said something along the lines of "why do we use RELU? Because it works better.. Why does it work better? We don't know for sure." Any field where the basic questions are still unanswered is going to make talented people think they are posers. In fact it's the only rational stance..
This has to be some sort of logic fallacy. With multiple offers you are guaranteed to be able to get higher pay, more time off, and/or better working conditions. You can't see the opportunity cost for one job offer, but tradeoffs to other jobs still exist. You might still be happier more productive and better qualified for a different job at a different company.
Yeah what a dog argument. Basically either shows the author has little comprehension of ml or he happened to design a terrible demonstration of small data issues.
The article isn't wrong. I count 15 words that are CS specific jargon in the Hello World statement. Couple this with some big lecture and mediocre professor who explains poorly, it's pretty painful intro experience.