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+ virtualenv I always forget to set that up. Also I never learned python packaging, with npm it was trivial.
The basic rule of thumb is npm is 'virtualenv by default' while pip is 'global by default'.
ES2015 imports took javascript back to 2008, before node and npm made it awesome.
use NPM and require if you are building tools for other people, that way they can implement your work without adding compilers and obscure configurations to their build. don't nobody want to use be forced to use alternative and backwards incompatible technology
use typescript and import for "business logic"
Going back to the Tensorflow C API and adding plotting + networking + async capability is a smart engineering choice. Will this project expand faster than Tensorflow Python to make it worth investing in? We will see in the coming months :)
Python has a larger ecosystem for data intensive application and pratictoners. As a language it's very easy to learn for JavaScript devs. The only "killer" feature JS may bring to the table would be client side, browser based inference that leverages GPU. But we're eons away from that.
I agree that JS is king in client side from PWA, desktop and native (with react), but also in async/API/distributed architecture. From a web server point of view, it took a large share of what usually went to Rails or PHP. It is a trend here to stay.
JS is also the largest community of devs, with 12M people very well versed in UX and ergonomics, something ML desperately needs to deploy faster.
Finally JS is a fast moving and innovative language due to many factors, from the fact we have several implementations, a light process for the tc39, transpilers, typescript/flow and wasm... What JS lacks from a syntax point of view may be adopted in months.
So wait and see, history is not written yet.
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Setting up a node env is arguably easier. An installer from the NodeJS downloads page includes both the Node runtime and NPM. One executable to get started. Python, on the other hand, requires a python installer, then a pip or conda installation script. Not to mention python vs python3 decisions.
But some version python comes pretty much with every system, then you only need to install tensorflow with pip.
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Setting up a node env is arguably easier. An installer from the NodeJS downloads page includes both the Node runtime and NPM. One executable to get started. Python, on the other hand, requires a python installer, then a pip or conda installation script. Not to mention python vs python3 decisions.
pipenv --three shell pipenv install pkg_1 pkg_ pkg_3 etc. Seems pretty easy to me. Plus, no one should be using Python 2 for any new project now, so that's not even a decision to bother with anymore.
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The basic rule of thumb is npm is 'virtualenv by default' while pip is 'global by default'.
This kind of thing is why people are saying npm is easier...
Didn’t he left the nodejs ecosystem because he said vocally that Go is so much better? Just curious what changed his mind...
> Pramod: Yeah, I like the programming model of Go. Using goroutines is so much easy and fun. In fact, we are using at work for building a distributed application.
> Ryan: Yeah, I think it’s… for a particular class of application, which is like, if you’re building a server, I can’t imagine using anything other than Go. That said, I think Node’s non-blocking paradigm worked out well for JavaScript, where you don’t have threads. And I think that a lot of the problems with kind of the call-back soup problem, where you have to jump into many anonymous functions to complete what you’re doing has been alleviated these days, with the async keyword, the async feature that’s in Javascript now.
> So, kind of the newer versions of Javascript has made this easier. That said, I think Node is not the best system to build a massive server web. I would use Go for that. And honestly, that’s the reason why I left Node. It was the realization that: oh, actually, this is not the best server-side system ever.
> Yeah. I think where Node has shined, weirdly, on the client side. So, doing kind of scripting around building websites. So, Browserify, for example. Kind of bundles up client-side Javascript. So, you can have all this server-side processing of client-side Javascript. And then, you know, maybe small servers to… maybe little development servers, and here and there, maybe some real servers serving live traffic. Node can be useful, or it can be the right choice for it. But if you’re building a massively distributed DNS server, I would not choose Node
[1] https://www.mappingthejourney.com/single-post/2017/08/31/epi...
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Setting up a node env is arguably easier. An installer from the NodeJS downloads page includes both the Node runtime and NPM. One executable to get started. Python, on the other hand, requires a python installer, then a pip or conda installation script. Not to mention python vs python3 decisions.
There's no python vs python3 decision to make. There's no (sane) reason to pick Python 2 in 2018 for new projects. Conda installer comes with Python prepackaged. So it's really a single exe and one CMD to get a Tensorflow env setup. And, of course, you have access to numpy, pandas, jupyter, PIL ...
That's totally exciting! Thanks to the author for enriching the ML ecosystem in JavaScript :) I didn't explore the full API yet, but already seeing the plotting functionality for functions is a tremendous win for ML in JavaScript. In case anyone is interested in doing ML in JS in 2018, there exists a larger article which I wrote a couple of weeks ago that tries to convey the state of the art of Machine Learning in Ja…