Propel – Machine learning for Javascript • Hacker News Board

Re: Propel – Machine learning for Javascript

#61

Post by dagw » Wed, Feb 28, 2018, 10:54 AM UTC

kapv89 wrote: post #60

kahnjw wrote: post #34

Earlier quoted context omitted.

And the full force of the entire machine learning research community (except for a few still on Lua/Torch).

We JS folks just need 1 good deep-learning system in JS. I really want that system to be propel as it leverages the work that has gone in on tensorflow. Let that piece fall into place, and just watch as the last bastion of python gets overrun.

How do you figure that deep learning is "the last bastion of python". From where I'm sitting deep learning is just the newest of many bastions.

Re: Propel – Machine learning for Javascript

#62

Post by dagw » Wed, Feb 28, 2018, 11:08 AM UTC

FridgeSeal wrote: post #58

ricardobeat wrote: post #46

Earlier quoted context omitted.

What's pipenv? Same as conda? Not using the system python also means installing python3 beforehand.

Pipenv is like virtualenv's but improved: https://docs.pipenv.org/ Conda is like pip, but focused only on the sciences/data stuff. Pip has everything that Conda has and more as it's the standard packaging solution for Python.

Conda is like pip

Conda is more like pipenv in that it does both package management and environment/version management. And while it's true that not every python package is in conda, that vast majority are and conda and pip play nicely together if you want to use pip to install some packages.

Also conda can be used to install both surrounding tooling (like gcc and make, super useful on Windows) and, in many cases, build dependencies and necessary C libraries. Something pip doesn't handle. Doing for example "pip install gdal" will very likely leave you chasing down third party dependencies, while doing "conda install gdal" will just work.

Finally, conda has recently added R support. So you can now manage your R packages and environments with the same tools as python. Super handy if you have project that uses both R and python.

Re: Propel – Machine learning for Javascript

#63

Post by kahnjw » Fri, Mar 02, 2018, 6:13 AM UTC

kapv89 wrote: post #60

kahnjw wrote: post #34

Earlier quoted context omitted.

And the full force of the entire machine learning research community (except for a few still on Lua/Torch).

We JS folks just need 1 good deep-learning system in JS. I really want that system to be propel as it leverages the work that has gone in on tensorflow. Let that piece fall into place, and just watch as the last bastion of python gets overrun.

>>...watch as the last bastion of python gets overrun

That is a naive point of view. The python community has been growing for decades [1]. Even if it is not growing as fast as javascript community, the growth is sustainable, and probably won't slow until the companies that rely on it for core parts of their infrastructure are gone (that could be 5 decades). Google, youtube, instagram, and countless other enormous corporations with trillions of dollars in combined market cap are dependent on it. Python isn't going anywhere.

[1] https://trends.google.com/trends/explore?date=today%205-y&q=...

Re: Propel – Machine learning for Javascript

#64

Post by darknoon » Sun, Mar 11, 2018, 5:53 PM UTC

cjalmeida wrote: post #25

sgslo wrote: post #17

Earlier quoted context omitted.

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 ...

You say this, but coremltools (convert from industry standard to Apple's ML framework) initially only supported python 2, so it was annoying to work with some code in Python 2 and some in 3.5.