101–110 of 157 posts
Why are all the em dashes missing from the PDF?
This may be a rendering issue. Some interaction of the Computer Modern font, the TeX layout algorithm, and Chrome's rendering engine sometimes ends up making em-dashes and minus signs invisible.
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In part because ML fails silently by design. Even if the code runs flawlessly with no errors, the outputs could be completely bunk, useless, or even harmful, and you won't have any idea if that is true just from watching The Number go down during training. It's not enough to know how to build it but also how it works . It's the difference between designing the JWST and assembling it.
I'm sure this happens, but do you think the problem is actually one of mathematical savvy? My guess would be that more machine learning projects go off the rails for want of understanding the data or the {business, research} problem.
Another issue is proliferation of data pipelines. The more distinct pipelines you have, the more painful they become to monitor. It is much better to minimize pipelines and do views on a small number. I think proliferations of models is a similar issue. It is often easier to build 4 models instead of 1 multi-task model, but monitoring/operational tasks grow more and more painful as you manage more models.
I have been working as an ML Engineer for a few years now and I am baffled by the bar to entry for these positions in the industry. Not only I need to perform at the Software Engineer level expected for the position (with your standard leetcode style interviews), but I need to pass extra ML specific (theory and practice) rounds. Meanwhile the vast majority of my work consist of getting systems production ready and hu…
What about asking for more money at the end? Multi-stage complex interview process eliminates more candidates. Some, like you say, will opt for a developer gig instead, probably because ML wasn't something they were interested in to begin with. That narrows down the list of candidates even more. Either "play the game" and ask for more money or don't play the game at all. Let employers pay extra for polished candidates.
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Having recently completed an MLE interview loop successfully at a top company, I'm wondering where you are getting asked complicated linear algebra questions in interview?
Hopefully you aren't equating "eigenvectors" to "complicated linear algebra question". But I agree, a lot of MLE roles don't get asked such things. I think the OP's guide is closer to interviews I've seen for phd programs.
They explicitly say something harder than eigenvectors in the GP.
I was imagining something involving the spectral theorem or something like that, ie. beyond the most basic linear algebra.
OPs guide seems to cover plenty of things I'd expect someone to learn in undergrad, I think I touched on almost all of this - except for stuff involving jax and recent CNN architectures, both of which can easily be supplemented online.
Question aside: using arXiv for distributing such interview questions, seems to me inappropriate. Is there any SEO trick behind it?
I have been working as an ML Engineer for a few years now and I am baffled by the bar to entry for these positions in the industry. Not only I need to perform at the Software Engineer level expected for the position (with your standard leetcode style interviews), but I need to pass extra ML specific (theory and practice) rounds. Meanwhile the vast majority of my work consist of getting systems production ready and hu…
I went through all that and am a SWE again instead of an ML engineer. The one thing I learned from all that? "The very best models are distilled from postdoc tears".
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That would just test syntax, though. Fizzbuzz tests logic. Your bug was a logic bug. To a certain extent you can dispense with mental logic by using a compiler. But the feedback loop is much slower. Thinking your logic through before feeding it to a compiler is like looking at a map when you're driving a car; you can cut off whole branches of exploration. Binary search is a particularly tricky logic problem in part b…
Ye I meant running it and then correcting the error. Concerning binary search I acctually implemented that in an ECU for message sorting. It took like a whole day, including getting the outer boundries one off too big in the first test run. Funnely enough the vehicle ran fine anyway. I would never pull that algorithm off correctly in an interview without training to, I think.
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I had an "implement binary search" interview once. I came away feeling like I was being interviewed for the wrong role. I don't understand how anyone could think that's an appropriate interview task for a DS position.
I'm an MLE and I get asked much harder questions than that. Implement a binary search seems ... fine?
The ML/DS positions highly competitive these days. I don't get why ML positions requires hard preparations for the interviews more than other CS positions while you do similar things. People expect you to know a lot of theory from statistics, probability, algorithms to linear algebra. I am ok with knowing basic of these topics which are the foundations of ML and DL. But I don't get to ask eigenvectors and challenging…
In part because ML fails silently by design. Even if the code runs flawlessly with no errors, the outputs could be completely bunk, useless, or even harmful, and you won't have any idea if that is true just from watching The Number go down during training. It's not enough to know how to build it but also how it works . It's the difference between designing the JWST and assembling it.
Earlier quoted context omitted.
It will be rat race when there are so many interview books and courses and websites. It was a not rat race before 2005, when there were only two reasons that one can solve problems like Pirate Coins or Queen Killing Infidel Husbands: the person is so mathematically mature that such problems are easy for them; the person is so geeky that they read Scientific American or Gardner's columns and remembered everything they…
You're missing the third category: people like myself who absolutely love this kind of riddles and destroy them in a few minutes, without any significance on their actual work abilities. I don't think I'm a bad engineer, but I'm certainly not the rock star you absolutely need for your team, but when it comes to this kind of “cleverness” tests, I'm really really good. I've had the “Queen Killing Infidel Husbands" (wit…
I had to fight my way into google by doing every bit of prep and practice to solve stupid questions and code quicksort but when I joined, nothing I did in the 12 years I was there required any of that. And I wrote high performance programs that ran on millions of cores (I did know some folks who needed that skill, like the search engine developers, or the maps engine, or the core scheduling algorithms in borg). The entire time I was there I tried to get people to understand the questions they're asking are just not good indicators of programming, but it was repeatedtly pointed out, the goal is to minimize false-positive hires.
I do admire your ability to solve problems like that quickly, always wished I could.