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Ask HN: How can a front-end developer dive into machine learning?

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Re: Ask HN: How can a front-end developer dive into machine learning?

#101

Post by yazr »

peakai wrote: post #41
wunderlust wrote: post #36

Earlier quoted context omitted.

Was your undergrad in computer science or did you 'hop' into the masters?

Liberal arts troll reporting. Starting my prereqs for a masters in CS this summer. It'll take me quite a bit longer to complete than someone who started with a BS in CS (basically I'm taking enough undergrad courses to fill several semesters, before even getting to MS work). However I was a developer for several years before this leap, and I feel pretty comfy with math things. Also working on reproducing papers to de…

What are the most complex paper you implemented ?

Did you throw enough CPU at it to compare results ?!

Re: Ask HN: How can a front-end developer dive into machine learning?

#103

Post by mrdrozdov »

potatoyogurt wrote: post #16
autokad wrote: post #6

it depends if you want to be a data engineer (lots of need for that), software engineer that developers code for data scientists (Software Engineer: Machine Learner - also lots of demand), or a data scientist. the latter, 'might' be a challenge. I started looking into linkedin profiles of data scientists of top tech companies after I realized there were more wharton mba's as data scientists than there where people wh…

That's probably because "data scientist" isn't a job description, it's a trendy title for a whole constellation of jobs that involve looking at data. I would expect that the Wharton grads are probably doing work that is fundamentally different from most people with hardcore academic stats backgrounds.

I think this sentiment is roughly correct. It's basically the same for programmer as there are many jobs that involve programming. Note that data science doesn't necessarily mean machine learning, and there are lots of data scientists who do powerful work with stats that doesn't involve anything that looks like ml.

The jobs for people working in machine learning tend to fall into: software engineer (machine learning), research engineer, and research scientist.

Yann LeCun has an excellent Quora Q&A where he delves into the differences of the roles. I do not have the link on hand but it is probably easy to find.

Re: Ask HN: How can a front-end developer dive into machine learning?

#104

Post by seibelj »

i-machine-learn wrote: post #89
seibelj wrote: post #49

Earlier quoted context omitted.

The same thing happened in the 90's, my coworker's sister got a "Certificate in HTML" and promptly found a job for $80k in 1998. These people wash out, I've been burned enough times by bootcamp grads that I won't hire them anymore

You are over generalizing. I am a bootcamp grad who specialized in undergrad in electrical engineering. I worked for a few years as a research for the one of the top tech universities in the country; I have found that I have a stronger math and physics background than many CS grads. However, many times when doing something I have been stopped by saying "wait aren't you a bootcamp grad? can you even understand this?"…

Yeah people with hard science degrees and/or from top schools, I'm less skeptical about. The guy who was a waiter 3 months ago and now saying he's a software engineer, very concerning.

Re: Ask HN: How can a front-end developer dive into machine learning?

#105

Post by biocomputation »

i-machine-learn wrote: post #89
seibelj wrote: post #49

Earlier quoted context omitted.

The same thing happened in the 90's, my coworker's sister got a "Certificate in HTML" and promptly found a job for $80k in 1998. These people wash out, I've been burned enough times by bootcamp grads that I won't hire them anymore

You are over generalizing. I am a bootcamp grad who specialized in undergrad in electrical engineering. I worked for a few years as a research for the one of the top tech universities in the country; I have found that I have a stronger math and physics background than many CS grads. However, many times when doing something I have been stopped by saying "wait aren't you a bootcamp grad? can you even understand this?"…

How is he over generalizing?

It's just a very simple fact that 90% of the bootcamp grads can't program their way out of a paper bag. In fact, most self-trained programmers are vastly better than even the best bootcamp graduates.

The problem with bootcamp grads is that they don't know what they don't know. And they don't know a lot. Undoubtedly some of them will turn out to be great programmers, but not after 3 months. Or even 6. Or even a year.

Re: Ask HN: How can a front-end developer dive into machine learning?

#106

Post by thatwebdude »

biocomputation wrote: post #105
i-machine-learn wrote: post #89

Earlier quoted context omitted.

You are over generalizing. I am a bootcamp grad who specialized in undergrad in electrical engineering. I worked for a few years as a research for the one of the top tech universities in the country; I have found that I have a stronger math and physics background than many CS grads. However, many times when doing something I have been stopped by saying "wait aren't you a bootcamp grad? can you even understand this?"…

How is he over generalizing? It's just a very simple fact that 90% of the bootcamp grads can't program their way out of a paper bag. In fact, most self-trained programmers are vastly better than even the best bootcamp graduates. The problem with bootcamp grads is that they don't know what they don't know. And they don't know a lot. Undoubtedly some of them will turn out to be great programmers, but not after 3 months…

I wasn't under the impression we were separating bootcamp from self-taught.

I took them both to mean "no formal schooling" and "self-taught". In my brief experience with I.T. training; some knowledge already had to be assumed.

Re: Ask HN: How can a front-end developer dive into machine learning?

#107

Post by seibelj »

throw_fraud_dev wrote: post #69
seibelj wrote: post #42

A lot of bootcamp / self-trained devs went into front-end JS for the money. Now that it's saturated, time to move onto the next buzz word. A foundation of CS fundamentals will still be lacking.

I'm a self trained dev (aka horrible person?) who's spent the last 8 years doing back end dev work - mostly C#, Java, Python and now Scala in everything from SV startups to a government research lab. Either I'm an outlier, or you're overestimating the importance of those cherished fundamentals (which can be picked up independently of a degree anyhow).

I think 8 years of experience plus solid references and projects speaks for itself. It's a resume that lists a 3 month boot camp, a github full of forked projects with no original commits (plus the obligatory ToDo app in rails), Senior Software Engineer title, $100k salary demand, leaving their first professional programming job after 6 months, can't speak knowledgeably about basic shit like IPC. I don't... have time... for this anymore.

Re: Ask HN: How can a front-end developer dive into machine learning?

#108

Post by dikdik »

jorgemf wrote: post #71
mrdrozdov wrote: post #25

In Feb 2015 I quit my job as a front end developer to learn more about machine learning. First, I went through the Recurse Center, which is a 3 month program sort of like a writing retreat for programmers. I learned a lot about Python and AWS in that time, and got an internship as a data engineer. In that Fall, I started a computer science master's. I've taken mostly courses in machine learning including: Machine Lea…

I work in machine learning and I don't think a 3 months course is going to transform you in a machine learning engineer. I think you need at least the time you took. You need to learn the maths, statistics, etc. Apply those tools to real problems, get some experience with different problems and techniques. And, finally, be involved in some type of research. Because machine learning is evolving so fast, you need to le…

Any insight for someone that already works as a bioinformatics scientist that wants to move into deep learning?

I've got the programming, math, some stats, and am currently involved in research, but I only know a little about deep learning. I'm currently working my way through the course.fast.ai deep learning courses and am going to do Part 2 when it is released.

Any other resources that would be useful for getting a job in this area? Best to just work on my own projects?

Re: Ask HN: How can a front-end developer dive into machine learning?

#109

Post by tonyedgecombe »

seibelj wrote: post #76
thatwebdude wrote: post #68

Earlier quoted context omitted.

About how long did it take for the washout to occur? Wanted to know for my own financial planning.

It is 100% possible to be an ace developer without a CS degree. However years of hiring experience has made my bullshit detector ring alarms with self-taught / bootcamp guys. If they have a hard-science degree it's less risky. Honestly I don't bother interviewing these people anymore without a warm introduction, it's hard enough to find good devs and the ratio of good to bad is so much worse with the self-taught crow…

My bullshit detector is ringing bells as well.

Re: Ask HN: How can a front-end developer dive into machine learning?

#110

Post by PeterisP »

AndrewKemendo wrote: post #98
jorgemf wrote: post #71

Earlier quoted context omitted.

I work in machine learning and I don't think a 3 months course is going to transform you in a machine learning engineer. I think you need at least the time you took. You need to learn the maths, statistics, etc. Apply those tools to real problems, get some experience with different problems and techniques. And, finally, be involved in some type of research. Because machine learning is evolving so fast, you need to le…

As a computer vision/ML applications engineer I disagree with this. What you describe is someone who is actively implementing cutting edge tech. That is VERY different than what 99% of people should be doing with ML which is: Spinning up some K80s on Azure, installing TF/CUDA/OpenCL, pulling existing pre-trained models off the shelf, and running inference on a novel data set. That's how you get into it as a garden va…

I would definitely extend this to running training as well, but I agree with the concept - for most people, it should be either transfer learning to adapt existing models to their data, or running training from scratch with currently known best practice methods, NN architectures and hyperparameters, but doing it on their particular datasets. Possibly by using mostly existing code and modifying mostly the data input/output routines.
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