Machine Learning in JavaScript

http://burakkanber.com/blog/machine-learning-in-other-languages-introduction/

by xd • 12 years ago

169 49 12 years ago

burakkanber.com

Already__Taken2• 12 years ago

This blog also contains a JavaScript physics series which is very cool.

Do hope this author writes more again it has been quite.

bkanber7• 12 years ago

Thanks! -- I am intending to write more, but the pace is sloooowww.

Joe8Bit2• 12 years ago

If you're looking for more on this, or some general purpose JS NLP you'd do worse than to checkout node-natural[0]

[0] https://github.com/NaturalNode/natural

frik2• 12 years ago

That's great, keep up the good work.

For some reason it's somewhat hard to find C-style science code examples in some disciplines. Python feels a bit like a plague in this respect. Everytime I have to wrap my head around while converting code to C-like language (C, C++, PHP, JS).

tlarkworthy2• 12 years ago

The distance to convert math to python is so much shorter than math to C or math to javascript.

You need something like numpy to make working in javasctipt easier before there will be a proliferation of of ML in JS.

I really love JS for its distribution and some of the visualizations are amazing. But the low level, numerically stable, matrix math primitives are sorely lacking.

Already__Taken2• 12 years ago

I feel the people doing heavy work with graphics APIs and 3D work with robots too will push this back into the javascript language given some time.

nashequilibrium2• 12 years ago

You need the love of the data science community and they have settled on python, and when they really want to scale they use Java. I noticed Julia becoming very popular and the twitter guys use scala for their stuff.

viana007• 12 years ago

For neural networks, you can use BrainJS

https://github.com/harthur/brain

nightski• 12 years ago

So the input/output pairs are a linked list of objects? Which then contain vectors comprised of linked lists? I am not very into JavaScript, but that right there must preclude this from doing anything significant in a reasonable amount of time?

LambdaAlmighty• 12 years ago

Only a question of time before the Machine Learning wave arrived at the arguably least suited--but certainly the most popular--platform!

There's money to be made with this combination. The field is ripe.

Good write up too.

code_scrapping• 12 years ago

I still view JS as a UI-oriented language, and I really don't know why would you want to implement processor-heavy algorithms in a browser environment, which need a lot of data and don't use the networking.

I would still stick to python. Or java. Or anything else which has a clear syntax and can run at a useful speed (I'm not mentioning C++ because of the coding overhead and dirty tricks which makes it a bit unfriendly for learning an algorithm)

xd2• 12 years ago

"Through this series of articles, I’ll teach you the fundamental machine learning algorithms using Javascript"

dangoor2• 12 years ago

Clarity of syntax is a matter of opinion (personally, I agree that Python is clearer than JS... Java, not so much.)

Implying that JavaScript can't "run at a useful speed" is wrong, using modern implementations. This is especially true for code that runs through lots of repetition as the just-in-time compilers in the JS engines do a remarkable job.

Not to mention that viewing JS as a UI-oriented language seems a bit out of date given the 40k or so packages for Node.js that are in npm.

JavaScript of today is pretty different than JS of 2007, and there are more changes coming with generators, iterators, destructuring, class syntax, arrow functions, promises, etc.

Joe8Bit2• 12 years ago

While I disagree with the comment you're responding to, and agree with yours, there are some interesting problems doing resource heavy operations in ML/NLP in an environment like Node that's inherently single threaded.

I'm actually adding multi-threading to classifier training in node-natural as we speak [0] so it's something I'm recently familiar with. Multi-threading in JS isn't new or particularly exciting (even less so is multithreading in ML/NLP applications) but the marriage of the two has led to a few interesting problems in JS's asynchronous/event based view of the world!

[0] https://github.com/NaturalNode/natural/issues/124

Edited for clarity

bkanber7• 12 years ago

Author here -- thanks for submitting, xd!

Let me know if you have any questions. I do intend to keep up with this series, although my pace is pretty slow at about one article every three months or so.

There are already a couple of comments about running ML in JS and how JS and the browser environment isn't terribly suited for heavy calculations. First: you're totally correct; second, I chose JS because it's

1) accessible -- whether you're Python or Ruby or PHP on the backend, you're probably comfortable with JS and

2) it demystifies machine learning -- you have to write your ML from scratch, without the help of all those wonderful Python libs, and I think this exercise shows you that it's not so mysterious after all.

Anyway, thanks for reading, and I'll poke in here throughout the day if you have questions.

xd2• 12 years ago

No no, thank you!

I've been building a data management platform for the last 8 years and we are now at the stage where we want to provide tools to help our customers get more from their data than just statistics. As my programming experience is mainly in PHP and JS this set of articles is helping me grasp ML rather than trying to wrap my head around a new language. I'm currently working on k-means clustering and re-implementing everything in PHP to get the best possible understanding I can .. my aim after that is to see how well I can implement things at an SQL level.

bkanber7• 12 years ago

Excellent, I'm glad to hear it! If you ever want to reach out, feel free -- email in my profile.

d_j_b• 12 years ago

This is great stuff - thank you very much.

all those wonderful Python libs

As a non-mathematician I have no understanding of how wonderful they really are, which is why this sort of thing is so valuable.

usamec• 12 years ago

"2) it demystifies machine learning -- you have to write your ML from scratch, without the help of all those wonderful Python libs, and I think this exercise shows you that it's not so mysterious after all." - you can demystify machine learning in any better language.

JS and PHP are slow, crappy and bug prone. Sane languages (like Python, C++) have tools to make your job easier (like numpy, blas, eigen and other libraries). They provide fast and reliable math routines so you don't have to worry about some eigenvalue decomposition, matrix multiplication and other problems.

bkanber7• 12 years ago

I'm not sure I understand the point you're trying to make. Are you telling me I should not have written this series? That it's somehow not valuable because you don't like JS? That I can't effectively teach basic machine learning concepts to interested people without forcing linear algebra onto them? That, as a teacher, I can't try to use any and all tools and techniques available to the group I'm trying to teach?

I've even explicitly mentioned that I'm staying away from algorithms that rely on linear algebra, because I'm trying to bring these concepts to people who may not have a CS or mathematical background.

breuleux• 12 years ago

JS isn't particularly slow any more, thanks to the massive efforts invested in the optimization of the various competing JS engines. It is generally faster than Python 3 (http://benchmarksgame.alioth.debian.org/u64/benchmark.php?te...) and not just a little. Just for the hell of it I compared node and python on naive fibonacci. That is anecdotal, of course, but node is 30 times faster. I do agree with you that JS has horrid, bug-prone semantics, but it's impressively well optimized.

I also agree that other languages offer better tools. For instance, Python has Numpy. However, that's written in C++, not in Python. You can write plugins for Node in C++ too, so nothing would stop someone from writing a Numpy equivalent for JS. You might even be able to run it in some browsers through something like Emscripten with a performance overhead of 2-3x (I think?)

zenocon• 12 years ago

Article looks really good! Look forward to longer read tonight. Minor nit: I'd stick with idiomatic JS style/formatting. Looks like you mixed in styles from some of the other languages (tab indentation, braces, etc.) This is always a religious argument, but I write a lot of different languages, and always just try to stick with the most popular idiomatic way, regardless of whether I care for it or not.

yohanatan• 12 years ago

Yea, 8-space tabs is a bit ridiculous. I prefer 2 or at most 3.

TeeWEE2• 12 years ago

X in JavaScript..... ugh

if all you have is a hammer, everything looks like a nail

bkanber7• 12 years ago

Have you read the article? I make it pretty apparent that JS is used primarily for its educational value :)

TeeWEE2• 12 years ago

To be honest i didn't initially. I just read it.

I think it is a noble thing to explain this in JS. But i don't think "because every body uses js" is a good reason to choose js.

However your specific use case makes sense. But in a broader sense I see more and more people fleeing to JS because its what they know.

morganherlocker3• 12 years ago

To those wondering why someone would want ML in JS, there are loads of reasons.

For starters, node.js, which makes most of the arguments regarding server/client moot.

Secondly, there are many client side applications for these types of algorithms as well. K-means clustering, for example, is already used by many mapping libraries to group together large numbers of points[1].

I personally use neural networks and affinity propagation in many of my applications for predictive analysis. This does not have to only be educational, or of a 'toy' nature.

[1] http://danzel.github.io/Leaflet.markercluster/example/marker...

nashequilibrium2• 12 years ago

Nodejs is for i/o, i know it has workarounds for long running tasks(threadpool) but it does not excell at that. Training your model, updating your model, validation, matrix factorization on large datasets etc, i just don't see how Javascript helps here. Maybe just taking the http request and dumping it onto a rabbitmq queue to to classify something but you still have a whole host of other stuff to deal with.

thrush2• 12 years ago

I think they are making the argument for capability rather than best of class. This is really exciting for Javascript and NodeJS devs right now because of the "Give me an inch and I'll take a foot" mentality.

morganherlocker3• 12 years ago

Nodejs is for i/o

Node is a general purpose language that can be used for all kinds of things. I switched from Python to node.js about a year ago for exactly the sort of tasks you are describing and could not be happier. Right off the bat I had huge speed improvements.

Also, io is one of the biggest issues with web based data analysis, so it really should not be underestimated. I can do more with less with node than I could with Python. This is especially true with long running tasks where a 1 minute processing time vs a 20 minute processing time might mean you need 1/20th the number of servers in a cluster ($$$).

Of course, this could be a pretty good argument for something even faster/lower level, but for me, node.js struck a good balance between performance and ease of development/ecosystem. As usual, YMMV.

One last point. The language you choose cannot always be the best language for every task you need. Typically you choose a stack based on the most common/important tasks in your infrastructure, then for less common tasks you just make it work with what the chosen language provides. In this case node.js does not need to be the best solution for ML, it just needs to check the box for being possible, so that devs who needed node.js for other reasons now have the ability to add ML to their toolbox.

ecesena• 12 years ago

Cool project! Have you already tried asm.js and/or measured performances?

frik2• 12 years ago

You cannot write asm.js by hand (in a sane way... it uses one big array for everything). It's meant to be translated from emscripten clang compiler project. So you can compile C/C++ code to asm.js.

But Javascript engines like V8 with its JIT are way faster than Python. You can even use typed arrays that give you almost native speed for such operations (e.g. matrix). I am coding a 3D game in WebGL and JS is as fast as Java when used in a modern fashion, though JS run in every browser

kajecounterhack• 12 years ago

For those who aren't familiar Andrej Karpathy has done a lot of cool stuff with ML in JS. Particularly he has a CNN library -- deep learning comes to JS!

http://cs.stanford.edu/people/karpathy/convnetjs/

http://cs.stanford.edu/people/karpathy/svmjs/demo/

Heather Arthur (npm libraries brain, classifier) has also done a bunch of cool stuff!

https://github.com/harthur

e12e• 12 years ago

Interesting, but I wonder about this:

… well, most of the time. There are some things you really can’t do in PHP or Javascript, but those are the more advanced algorithms that require heavy matrix math.

Leaving out javascript (in the browser), it sounds like an odd statement to make about php -- after all one of php strengths is how easy it is to link with c-libraries (or other with c ffi)? Among other things I quickly found:

http://www.php.net/manual/en/intro.lapack.php

perimo• 12 years ago

I kicked around with some JS manifold learning stuff[1] a while back for essentially the same purpose: practice in writing things from scratch, while making it easier for other people to play with.

[1] https://github.com/perimosocordiae/js_manifolds

Machine Learning in JavaScript

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