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Deep Learning Interviews book: Hundreds of fully solved job interview questions

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Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#111

Post by jhgb »

PeterisP wrote: post #40
TrackerFF wrote: post #37

Earlier quoted context omitted.

Likewise, in the military, the use of countersigns have been designed to make non-native speakers stand out - should the countersign be compromised. For example, in WW2, Americans would use "Lollapalooza", as Japanese really struggled with that word.

That's more of a shibboleth than a secret, which is literally a practice as old as the Bible - "And the Gileadites took the passages of Jordan before the Ephraimites: and it was so, that when those Ephraimites which were escaped said, Let me go over; that the men of Gilead said unto him, Art thou an Ephraimite? If he said, Nay; Then said they unto him, Say now Shibboleth: and he said Sibboleth: for he could not frame…

If you combine a shibboleth with a secret, how do you call it? Shibbecret?

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#112

Post by jhgb »

8note wrote: post #22
1970-01-01 wrote: post #6

This book has fun problems! Example: During the cold war, the U.S.A developed a speech to text (STT) algorithm that could theoretically detect the hidden dialects of Russian sleeper agents. These agents (Fig. 3.7), were trained to speak English in Russia and subsequently sent to the US to gather intelligence. The FBI was able to apprehend ten such hidden Russian spies and accused them of being "sleeper" agents. The A…

Really small? How many russians in america are actually sleeper agents?

That would be a good argument in a general case but the premise of all Russians present at the diplomatic gathering being secret agents is clearly stated.

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#113

Post by pasquinelli »

hintymad wrote: post #44
mcemilg wrote: post #41

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…

A reason for such requirements is similar to that that software engineers need to leetcode hard: supply and demand. Prestigious companies get hundreds, if not thousands, of applications every day. The companies can afford looking for candidates who have raw talent, such as the capability of mastering many concepts and being able solve hard mathematical problems in a short time. Case in point, you may not need to use…

and yet we're also told that tech companies can't get enough people.

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#114

Post by eez0 »

dekhn wrote: post #110
littlestymaar wrote: post #70

Earlier quoted context omitted.

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…

If somebody asked me logic/brainteaser questions like that, I would politely stop them, explain that if they're asking me that question I'm not a good match for the company, and if they would like to ask a better question, I'm open to it, but otherwise, we can end the application process now. I did that recently with a junior eng who asked me a leetcode question literally with the same exact test data as the leetcode…

> If somebody asked me logic/brainteaser questions like that, I would politely stop them, explain that if they're asking me that question I'm not a good match for the company

This is exactly what I started to do after I was asked a leetcode-based question for a SRE manager position.

It turned out that by making clear my "profile", I stopped to have bullshit interviews and started to get ones more aligned to actual daily work.

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#115

Post by fault1 »

crate_barre wrote: post #84
jollybean wrote: post #78

Earlier quoted context omitted.

But if there is an abundance of supply, the company has to use some kind of filter. Testing for geekyness and ability to solve tricky coding math problems, seems like a rational way to do that. If companies were starving for talent because 'nobody could pass the test' - it would be another thing. But they have to set the bar on something, somewhere. I can't speak to AI/ML but I would imagine it might be hard to hire…

There’s an abundance of supply of people with masters degrees in machine learning? How’s that possible? I thought this shit was supposed to be hard. Has humanity just scaled way too hard or something, because if we’re having an abundance of supply in difficult cutting edge fields to the point where they also have their own version of Leetcode, then what hope do average people have of getting any job in this world? Or…

> There’s an abundance of supply of people with masters degrees in machine learning? How’s that possible? I thought this shit was supposed to be hard.

I think it's just a matter of proliferation of these types of programs, as well as a large supply of students.

Also, the average qualification of people working in ML is probably no longer a Ph.D, like it used to be. This is arguably because deep learning techniques require less involved math to understand, and are more focused on computational methods that work well.

So the field has probably saturated. When I got involved with ML for the first time (well, really, statistical signal processing) in the mid 2000s, the field was kind of dead, and very high qualified postdocs had tough time finding jobs.

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#116

Post by ivanamies »

angarg12 wrote: post #88

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…

As an "ML Engineer," this is both true and very funny

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#117

Post by flubflub »

devoutsalsa wrote: post #79
mcemilg wrote: post #41

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…

I figure the best way to prepare for an ML job is to pull out the nastiest working rat’s nest of if statements you’ve ever written & claim it was autogenerated by an adversarial network (which was you fighting with your coworkers over your spaghetti code).

This really made me laugh, thanks.

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#119

Post by Jensson »

dekhn wrote: post #106
angarg12 wrote: post #88

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…

there's a bunch of gatekeeping to get into ML. Part of it is that ML people don't want non-ML people to know just how much of what they do is drudgery and how little of it is exciting math, or have competition from people with similar skills. And those roles come with a lot of prestige. 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 a…

Getting state of the art performance in ML requires a lot of intuition about equations though. I've seen some of the top ML engineers work at Google, they all have a really good understanding of math, how formulas translates into measurable results etc. An ML education or research background seems less important, if you have that from studying physics or math or anything then it still translates.

I feel the biggest problem for people without an ML background is that you'd think "I don't know what I'm doing, I can't get hired for this job!", but fact is that people with ML backgrounds mostly don't know what they are doing either. They just get standard results by applying standard libraries, any programmer with some math skills could do the same, it is no harder than learning a frontend or backend framework, people just think it would be harder so they lack confidence about it. There are some gotchas you got to learn, but there are a lot of gotchas in both backend and frontend as well.

Re: Deep Learning Interviews book: Hundreds of fully solved job interview questions

#120

Post by agentofoblivion »

I commend the author’s effort, but this is not reflective of any interviews I’ve been part of, which is many across several industries and levels. Bayesian Deep Learning? Chapter 2 in Kindergarten? If anyone asked me a question on that, I would kindly ask them to eat shit.
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