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Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

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Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#131

Post by wyclif »

tekkk wrote: post #91
imh wrote: post #71

Stop focusing on MOOCs and youtube videos and study textbooks. Do exercises. Treat it like academic studying, and you'll end up with a decent education. It's important, because it's often easier to make a thing work okay than to understand why it works, so you'll get false confidence working through a tutorial. But then you want to apply that to something else and it doesn't work quite right, you won't know why it do…

You're not going to learn much of anything by just reading a ML/AI book. Well you gotta be pretty good at math to understand everything, my suggestion is to enroll on some ML/stats course and start working on basics. It's long and hard road, and if you're not comfortable with math in general i'd reconsider investing too much time on it. I'm doing it yet i'd much rather do software engineering. Much more practical wit…

I'd need a lot more remedial mathematics before I could get any mileage out of those ML/AI book recommendations. I haven't touched mathematics in a strict sense since my senior year of high school Calculus (I majored in the humanities), so I think you're absolutely right. People like me would need to spend a lot more time learning things like discrete math and statistics before moving up to these books.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#132

Post by nidhalbt »

imh wrote: post #71

Stop focusing on MOOCs and youtube videos and study textbooks. Do exercises. Treat it like academic studying, and you'll end up with a decent education. It's important, because it's often easier to make a thing work okay than to understand why it works, so you'll get false confidence working through a tutorial. But then you want to apply that to something else and it doesn't work quite right, you won't know why it do…

I agree that MOOCs, particularly in areas such as math and physics, are woefully insufficient. Nevertheless, videos and MOOCs still have their place, because they help you formulate the questions you need to answer. They help you know what unknowns you don't know.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#136

Post by agentofoblivion »

jeff76 wrote: post #124
agentofoblivion wrote: post #115

Earlier quoted context omitted.

I think it’s unlikely to become expert in all of those things. If you do, it’s over the course of an entire career, not to get started. I guess it comes down to how much expertise is “enough” for you. Naturally, if you split your time across 3 domains you won’t be as expert as someone who dedicated all their time to going deep in one. In the context of a big company, I think it makes sense to have a specialized workf…

This answer makes sense. I suppose my question is more along the lines of, if someone is specializing in deep learning in a PhD program then shouldn’t they at the very least be able to implement models and also know optimization tricks? In other words shouldn’t they be able to develop enough skills to go deep in one area but also know enough to be dangerous in the other three domains?

I think I agree with you with the caveat that it would depend on what they're researching. If they're researching new model architectures, I don't think it makes sense for them to try to implement the algorithms from scratch in C++/CUDA to do distributed GPU training--why not just use TensorFlow? But if you're researching distributed tensor computation, then that's your bread and butter.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#137

Post by agentofoblivion »

scatter wrote: post #125
agentofoblivion wrote: post #98

I basically did what you’re talking about. Masters in physics, then went into semiconductors as engineer and materials scientist, then switched to Data scientist at a bank for 18 months, and now have been a research scientist in AWS for almost two years. In Amazon, it’s easy to move around, but not between job families. I think it’s a bad idea to join as a SWE and try to transfer because they want people that have do…

Great reply. Just out of curiosity, did you end up giving your semiconductor job before joining the start up with a data scientist title ? I am deep into semiconductors, and am facing the dilemma of giving up my expertise so far, to join a startup as an entry level engineer. I have done a couple of MOOC specializations and am trying to find projects within my industry to gain some credibility. Also trying to stay act…

In my particular case, I did quit my job before I got my "real" Data Science position. I can't recall exact timelines, but I think I had already lined up the relationship with the startup.

The reason I did this is because there just wasn't enough hours in the day, and my job was taking ~10 hours a day with commuting...etc. It was a risk, but the idea was that I would be able to transition much more quickly if I worked full-time towards it. I also had the financial savings to support myself for 6-9 months and was willing to get a part time job if necessary. Once it became clear that my job's only purpose was to pay the bills in the context of my goals, and I had enough to pay the bills for the near future, it was clear that quitting was the easiest way to free up a lot of time.

This turned out to be the best decision of my career, but YMMV. I doubled my salary in less than 2 years. It's also nice to be part of an industry that isn't so cost-sensitive. I also have a skill set that's in much higher demand, so you can live almost anywhere and there's a ton of companies that want/need it. With semiconductors, you're much more limited.

It's true that you're giving up some expertise and will start in a less senior position in a different field than if you stayed in semi. Sticking around because you have experience is classic Sunk Cost Fallacy. Think 5 years down the line. If you leave now, you'll have 5 years experience in ML. You'll definitely be giving something up if you leave, but there's huge opportunity cost if you don't leave.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#138

Post by imh »

jatins wrote: post #130
imh wrote: post #71

Stop focusing on MOOCs and youtube videos and study textbooks. Do exercises. Treat it like academic studying, and you'll end up with a decent education. It's important, because it's often easier to make a thing work okay than to understand why it works, so you'll get false confidence working through a tutorial. But then you want to apply that to something else and it doesn't work quite right, you won't know why it do…

My experience has been different. "Academic Studying" can be hard with a full time job, and there is often a wide gap between what you learn in books and what you do at the job. For purely professional purposes, it's probably a better idea to take a non-academic approach.

Yeah, it's super hard with a full time job. That's why I recommend setting a low X pages per day target. Making sure to make just a few pages of progress per day really adds up quickly. You likely won't progress as fast as if you were a full time student, but that's okay. It still adds up fast enough.

A minimum of 5-10 pages a day for 6-12 months seems pretty reasonable for a career change into a competitive field.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#139

Post by scatter »

agentofoblivion wrote: post #137
scatter wrote: post #125

Earlier quoted context omitted.

Great reply. Just out of curiosity, did you end up giving your semiconductor job before joining the start up with a data scientist title ? I am deep into semiconductors, and am facing the dilemma of giving up my expertise so far, to join a startup as an entry level engineer. I have done a couple of MOOC specializations and am trying to find projects within my industry to gain some credibility. Also trying to stay act…

In my particular case, I did quit my job before I got my "real" Data Science position. I can't recall exact timelines, but I think I had already lined up the relationship with the startup. The reason I did this is because there just wasn't enough hours in the day, and my job was taking ~10 hours a day with commuting...etc. It was a risk, but the idea was that I would be able to transition much more quickly if I worke…

Would you be open to have a brief conversation on the phone for advice? My email is knariks@gmail.com.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#140

Post by espeed »

espeed wrote: post #114
ryanjodonnell wrote: post #31

Earlier quoted context omitted.

We gotta stop saying 'FAANG' when MSFT is the arguably the top tech company around these days.

GANMAF

...or GANFAM to better emphasize a more healthy spirit of competition and collaboration.
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