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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?

#41

Post by peakai »

wunderlust wrote: post #36
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…

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 develop chops, in my spare time so my dev skills don't go to nil. Excites me since I've always wanted to grow to this level as a dev, I just never had an excuse to go for the CS degree till ML came along.

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

#44

Post by emsal »

luked22 wrote: post #38
3chelon wrote: post #34

Your question says "utilize" machine learning. I was in the same position. It struck me that rather than go off and try to catch up with half a century's research, and contribute nothing, I'd be better off utilizing machine learning in my front-end work. So I have started using IBM's Watson platform, and some of Google's AI tools. I was specifically interested in speech processing applications (I have some background…

I have no clue about Watson and Machine Learning, I mean I've talked to people and quickly glanced at the platforms. But in terms of the speech processing, does that not require any back-end at all? I'm assuming your using the browsers API to capture sound and then passing this off to Watson in some back-end method to analyze? Or can this seriously be done all fron-end? Pretty amazing if so.

It's not that the actual ML computation is done client side -- that would be way too slow. With Watson and many other ML platforms, you're leveraging someone else's (IBM, Google, Microsoft, Amazon, etc.) computing power.

Some people have made javascript-based ML models to run in the browser (I think some were made for this course[1]), but these are for educational purposes rather than actual use.

[1]: https://cs231n.github.io/

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

#45

Post by 3chelon »

luked22 wrote: post #38
3chelon wrote: post #34

Your question says "utilize" machine learning. I was in the same position. It struck me that rather than go off and try to catch up with half a century's research, and contribute nothing, I'd be better off utilizing machine learning in my front-end work. So I have started using IBM's Watson platform, and some of Google's AI tools. I was specifically interested in speech processing applications (I have some background…

I have no clue about Watson and Machine Learning, I mean I've talked to people and quickly glanced at the platforms. But in terms of the speech processing, does that not require any back-end at all? I'm assuming your using the browsers API to capture sound and then passing this off to Watson in some back-end method to analyze? Or can this seriously be done all fron-end? Pretty amazing if so.

Well, I am currently developing a full-blown back-end service using AWS containers, but for a prototype I got it going as a simple Python script, based on an outline I found on github. Took a few hours.

Basically you get your source speech as an uncompressed WAV file, create an IBM Bluemix account (free trial), create a Watson "app" on the site (basically gives you some credentials for calling the API), and then write a script to upload your WAV file to the API and decode the JSON response.

It gets more complex when you want to start parallelizing the process to make it faster, and dealing with the results in an intelligent manner, but the initial proof of concept is remarkably easy.

If I recall, the Google one was even easier - no script at all, did it all with curl I think.

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

#46

Post by ardivekar »

mrdrozdov wrote: post #37
wunderlust wrote: post #36

Earlier quoted context omitted.

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

My undergrad was in computer science, although I would say this wasn't the case for most of my classmates. There were a lot of students from other engineering fields (like Mech E or civil), Math, Stats, physics, bio, and business.

Which college and which program, if you don't mind sharing?

Edit: for the Master's degree.

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

#49

Post by seibelj »

thatwebdude wrote: post #43
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.

u mad, bro?

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

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

#50

Post by mooreds »

I would suggest running through a tutorial or two using one of the hosted machine learning options (Amazon has one I am working with right now).

This will let you focus on the essence of machine learning (data gathering and cleansing, interpretation) rather than the mechanics. The gathering of data and building of intuition about results are by far the hardest parts of machine learning, in my experience and reading. This is especially true if you are just getting started.

Plenty of time to focus on the mechanics later.

(Full disclosure, I am working on a ebook about Amazon machine learning link in profile.)

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