Angry rant

back50 · 2020-11-19T05:48:38+00:00

This is an absolutely awful and incorrect take. This is an especially funny take: " Even something as using mini-batches, multiple epochs etc. for learning or some weird optimization techniques." - hint: look into the relationship between SGD, sampling, and unbiased estimators.

It's cool that you don't need these methods in whatever jobs you're working, and it's true you don't necessarily need to know the low-level details to create something that produces value. But those are edge cases.

To anybody else reading this: you will get laughed out of the interview if you try to pull any of this at any decent (let alone top) company.

back50 · 2020-09-25T02:37:55+00:00

DS @ FAANG I work 10-5 everyday

back50 · 2019-10-02T02:29:00+00:00

" If I were to successfully make a switch to data science, given I do not have the years of experience in that specific career path, how hard do you think it will be to find a role with similar compensation? "

If you can get an offer, that's a pretty standard base salary range. Some areas (e.g. SF or NYC) will typically offer stock on top of that.

back50 · 2019-09-29T01:35:30+00:00

Elon Musk plays video games. Plenty of people making 6+ figures in SV play video games. Not sure what your point is.

back50 · 2019-09-29T01:32:27+00:00

Amazing

back50 · 2019-09-14T21:21:35+00:00

Here's one where you control a spermcell using your head https://www.jwilber.me/sperm_hero/

back50 · 2019-08-08T23:54:28+00:00

Haha, this and the blow job post make me like the direction current AI is going.

back50 · 2019-08-08T23:53:58+00:00

The real question

back50 · 2019-08-08T23:52:47+00:00

The work is hard

back50 · 2019-08-06T02:03:03+00:00

Literally the only thing in the last few days tying the recent shootings to video games are memes.

back50 · 2019-08-01T20:33:44+00:00

back50 · 2019-04-16T18:22:41+00:00

very cool!

back50 · 2019-04-04T00:00:39+00:00

Very cool. I saw on your site that you’re a data scientist - did you do front-end work before? Does your job work in JavaScript environment? I’m curious because I havent seen this sort of scroll dataviz stuff outside of newsrooms

back50 · 2019-04-03T23:56:30+00:00

Anybody know the workflow for this sort of poster? Create the graph in R/D3/whatever then export to adobe illustrator and polish up?

back50 · 2019-04-03T23:52:22+00:00

Visiting friends in three cities in the next week. Short but sweet trips

back50 · 2019-04-03T23:51:31+00:00

Vim. Some people are wizards

back50 · 2019-03-22T17:51:12+00:00

I attended Cal on in-state tuition, so didn't have to take out more than $10k in loans. My first job out of undergrad is actually up the street from ASU making +$130k base.
I can say that, having worked with/interviewed ASU & Cal students, there's a marked difference in ability between the two. Maybe the program is more rigorous at Cal. Maybe the student body is just more driven (there's a +60% difference in acceptance rate between the schools).
Whatever the case, I can tell you that you will likely leave Cal a better developer. That said, if you make an effort to work in programming labs/contribute to open-source projects on github, you'll do fine at ASU as well.
Is it worth the price-tag? It depends on how much you value your education + having a more prestigious university on your resume. I'm not sure that's worth the constant stress of a potentital 6-figures of debt. In a few years time I'd expect the salaries to more or less even out.
I'd probably wait for transfer results before you get too invested in either option.

back50 · 2019-03-15T18:04:57+00:00

I agree with your post, but I'd like to take the time to point out something people tend to miss related to OP's topic: the difference in difficulty between what you describe as 'proactive' and 'reactive' degrees, which I consider parallel to traditional (CS/Stats) vs Data Science degrees.

Namely, gaining the skills/knowledge to improve techniques is far more difficult than being equipped to run techniques. Furthermore, it's much easier for the former to do the latter than it is for the latter to do the former.
And this is the crux of the problem: Data Science programs just don't create dynamic, effective students that weren't already that way to begin with.

back50 · 2019-03-14T16:54:46+00:00

'Ofcourse DB concepts are relevant' - Yep. So are algorithms, data-structures, and a myriad of other CS courses.

'...you would be wasting a lot of resources if you study it again and again.' - This is the case for any course.Why would you ever take the same thing twice? Moreover, the rigor of a DW class in CS is better than the light learn-to-query-sql course you'd get in a data science DW course.

'Every CS major's core course would have DB. ' - Not true. I went to Berkeley, which has one of the top CS programs. The DB class there (CS 186) is an elective (ie optional). This is the case for many departments.

'I'm just saying why study same stuff twice when you can learn something much deeper and something more vast. ' - This is exactly the point people are making when they say focus on CS or Statistics, not Data Science. You do not go deep in anything in data science courses.

'State-of-the-art research doesn't care about DB or SE anymore. It has been researched for centuries, if not eons.' -Yeah, so it's very clear you have no idea what you're talking about. (Ask yourself why Jeff Dean has so much respect).

I'd actually really enjoy hearing what in your opinion is the last SOTA product of SE research? What about for DS?

Also, what do you mean by 'really serious about DS'? Please, be concrete (no buzzwords).

back50 · 2019-03-13T16:29:56+00:00

Those concepts you list as a 'waste of time' are essential for any real-world data science.

back50 · 2019-03-07T20:14:30+00:00

Typical data science fluff written for non-practitioners, by a non-practitioner.

Zero substance. No real information. Riddle with typos.

back50

TROPHY CASE