Python 2.7 is frozen. It just get security updates. The community is investing in Python 3. All the main numerical libraries are already compatible with Python 3 and, unless you need a very specific library, there is no reason to start developing new projects in Python 2 nowadays.
Don't know what has changed since 2014. My perception is that Armin feels he's been pigeonholed as being more anti-Py3 than he actually is, at least with the state of Python in 2016:
> In fact, I myself campaigned for some changes to Python 3 that made it possible to achieve better ports (like the reintroduction of the u prefix on Unicode string literals) and the bulk of my libraries work on Python 3 for many years now. It's a fact that in 2016 the problems that people have with Python 3 are different than they used to have before.
As per public statements, Google has ~100 million lines of Python code. Also, Google has used Python very heavily from the start, meaning that some of that code was written in Python 1.x or early 2.x days, before the language had packages, before standard modules like 'logging' or 'unittest', even before booleans(!).
It's just a lot of code to migrate. It takes time.
Disclaimer: Work at Google, wrote some of that code.
Jupyter switch really easily from Python2.7 to Python 3 to C# because the front end and backend are separated. Not sure why they are having issue here.
I know its free. This is begging, not ranting. For those of us who code/automate for our business and who are not data/ml scientists, can we PLEASE have real world examples and an abstraction layer or two so we can start using these tools as part of our workflows?
I have two classifiers running for my business with about 70% accuracy. Good enough for my purposes. So grateful to the bloggers kind enough to provide real world examples and sample code that helped me understand and apply this stuff to my business.
Anything that makes ML less of a walled garden is most appreciated.
ML is gonna be the next commodity on the stack. It takes time, but considering some of the complexity, I'm impressed by the speed at which this is becoming reality.
The demo notebook has a TensorFlow example, which is a machine learning library.
However, it’s not a full ML example, which is what the OP wants. (but since the VM has only 2 vCPU, training a model with TensorFlow may not be pragmatic)
While this doesn't provide real world examples (yet), we are trying to make a free list of short, concise, to-the-point tutorials for anyone to get familiar with the basics of Deep Learning. Best part is that each item is a wiki, so you can make it better and you'll automatically be credited in the sidebars. Leave any suggestions on the structure in the comments. Here it is: https://www.commonlounge.com/discussion/81f5bbcfea4e44b9b2bd...
What do you need classifiers for in your business? I mean, why did you need to build it yourself? Is it like spam filtering of some sort? I'm surprised you had to build it yourself, in this day and age, as there would be services that provide this?
I don't think it's a production service, but I've talked to a couple of people involved and it sounds like it's getting a good response when it's been introduced in educational environments.
Does this support real-time editing with someone else (similar to Google Docs?).
I've been using JupyterLab [0] + Google Drive [1] plugin for this. It uses Drive's API for doing real-time collaboration and let's you code in real time with someone else. It's the only solution I've found for this that doesn't require you to pay an arm to use.
I quite like the theme. Even though Anaconda 5 has finally upgraded Jupyter's look for me and I need Python 3, the visuals and look are... cute. I hope they get open sourced.
nice. same as gryd (https://gryd.us) which is free for students and has a tight autograding integration + sharing etc. would like to see if colab will be maintained and expanded going forward or if this is it.
As u/halflings pointed out, the current version of Colaboratory offered was spun off some time ago (3+ years ago?) from this jupyter-associated repo: https://github.com/jupyter/colaboratory
In another begging-not-ranting, I was surprised that Colaboratory currently only supports 2.7x. It looks like it began around 2014. IIRC most of Google's projects were 2.x upon public release (Tensorflow, the API client) but have since ported over. Jupyter notebooks and iPython, too. Anything particular about Colaboratory that makes a 3.x-port a time-intensive feature, or just something that was not needed during internal development?
(Asking as a casual Jupyter user with no knowledge about what code/features is specifically 2.x bound)
This is pretty cool! I know it's new and all, so maybe I'm getting ahead of myself when saying that it would be nice if it supported other languages aside from Python. I know that iPython supports Ruby, Perl and Javascript, and there's a plugin for Julia, but it doesn't appear to be supported right now. I am still on the waiting list to play around with this however.
Also, integration with Google docs for the purposes of data processing and data handling would be incredible! But that's just me dreaming.
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[ 4.7 ms ] story [ 151 ms ] threadHowever, the VM uses Python 2.7. (Per the FAQ, Python 3 support has no ETA)
Don't know what has changed since 2014. My perception is that Armin feels he's been pigeonholed as being more anti-Py3 than he actually is, at least with the state of Python in 2016:
http://lucumr.pocoo.org/2016/11/5/be-careful-about-what-you-...
> In fact, I myself campaigned for some changes to Python 3 that made it possible to achieve better ports (like the reintroduction of the u prefix on Unicode string literals) and the bulk of my libraries work on Python 3 for many years now. It's a fact that in 2016 the problems that people have with Python 3 are different than they used to have before.
It's just a lot of code to migrate. It takes time.
Disclaimer: Work at Google, wrote some of that code.
[0] https://stackoverflow.com/questions/46941308/python-3-suppor...
I have two classifiers running for my business with about 70% accuracy. Good enough for my purposes. So grateful to the bloggers kind enough to provide real world examples and sample code that helped me understand and apply this stuff to my business.
Anything that makes ML less of a walled garden is most appreciated.
https://machinelearningmastery.com/deep-learning-with-python...
Really neat intro, simple examples, using high level libraries (Keras and TF).
However, it’s not a full ML example, which is what the OP wants. (but since the VM has only 2 vCPU, training a model with TensorFlow may not be pragmatic)
https://wikitech.wikimedia.org/wiki/PAWS
I don't think it's a production service, but I've talked to a couple of people involved and it sounds like it's getting a good response when it's been introduced in educational environments.
Supports more than Python 2.7: https://notebooks.azure.com/help/jupyter-notebooks/available...
(disclaimer: work for Microsoft (though not Azure)).
I've been using JupyterLab [0] + Google Drive [1] plugin for this. It uses Drive's API for doing real-time collaboration and let's you code in real time with someone else. It's the only solution I've found for this that doesn't require you to pay an arm to use.
[0] https://github.com/jupyterlab/jupyterlab
[1] https://github.com/jupyterlab/jupyterlab-google-drive
Just tried azure, looks legit. 2.6, 3.5, 3.6, and R
Is there a guide to installing frameworks in azure notebooks? I don't mind paying for using it.
I’m excited to see others getting access to this tool.
If anyone else has access already, here's a tutorial I wrote on generating L-system fractals:
https://colab.research.google.com/notebook#fileId=1pftvKmXYN...
(This is the first time I've used colab outside of Google so let me know if it doesn't work!)
Colab is the "mature" verison of Jupyter Colaboratory, which was previously only used internally at Google.
But it's great to have more options!
I've used it in my class for those Windows users who always have trouble installing things and it's worked very well so far.
https://mybinder.org/
I don't see anyway of selecting python3, any one found the option? Or are they only supporting Python2?
https://stackoverflow.com/questions/46941308/python-3-suppor...
In another begging-not-ranting, I was surprised that Colaboratory currently only supports 2.7x. It looks like it began around 2014. IIRC most of Google's projects were 2.x upon public release (Tensorflow, the API client) but have since ported over. Jupyter notebooks and iPython, too. Anything particular about Colaboratory that makes a 3.x-port a time-intensive feature, or just something that was not needed during internal development?
(Asking as a casual Jupyter user with no knowledge about what code/features is specifically 2.x bound)
Also, integration with Google docs for the purposes of data processing and data handling would be incredible! But that's just me dreaming.
https://datascience.ibm.com/
Just use Azures jupyter notebook environment if you need a no-setup in the cloud notebooks.