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Pramit Choudhary
@pramitchoudhary
If you got a chance to try Skater, would be great to know about the things you liked and things where we can improve
We at DataScience.com see a need for Effective Interpretation of Statistical / ML model. How do you feel ?
Pramit Choudhary
@pramitchoudhary
here is a feedback form: https://goo.gl/forms/m0JbnPQP6pK5ZN3V2
here is an interesting article on the accountability of ML models,
https://www.propublica.org/article/making-algorithms-accountable
Aaron Kramer
@aikramer2
Release v1.0.3 now live on master, will be pushing to pypi and conda soon. See notes here: https://github.com/datascienceinc/Skater/releases/tag/v1.0.
Pramit Choudhary
@pramitchoudhary
thanks @aikramer2
Pramit Choudhary
@pramitchoudhary
datadave
@datadave
@aikramer2 @pramitchoudhary woot! Congrats guys.
Pramit Choudhary
@pramitchoudhary
thanks @datadave
Aaron Kramer
@aikramer2
@pramitchoudhary lets push v1.0.3 to pypi
Pramit Choudhary
@pramitchoudhary
@aikramer2 just saw ur IM, not sure why i didn't get notified
ya, lets do that. Have been busy with new features. Will update conda and pypi in the next couple of days. If you get a chance to do it before, that works too
Pramit Choudhary
@pramitchoudhary
Updated the pypi registry with v1.0.3 (https://pypi.python.org/pypi/skater)
Having been adding new features for text interpretability, might need a hand for code review before the new release contains those changes
will update here
Pramit Choudhary
@pramitchoudhary
@aikramer2 possible to update conda repo with the new version ?
Pramit Choudhary
@pramitchoudhary
Good-morning guys
Pramit Choudhary
@pramitchoudhary
Here is another idea to look into
https://openreview.net/forum?id=rkRwGg-0Z
What do you guys think about it ?
Pramit Choudhary
@pramitchoudhary
Welcome Brett
Brett Olmstead
@Brett777
Hey guys
Am interested in including some Skater in a demo
Some of the demos I show use H2O models
What are the currently supported libraries?
Just SKLearn?
Pramit Choudhary
@pramitchoudhary
We had started work on supporting h20 but couldn't complete it. In-terms of supporting libraries, we have examples for python/R based models/third party vendors(indico.ai, algorithmia), deep-learning framework like keras
It would be great, if you could take a shot at H20 models and see how we can change improve the library to enable a more native support. Looking fwd to collaborating
Pramit Choudhary
@pramitchoudhary
This year NIPS had a lot of traction in-regards to Model Interpretability
Here is the keynote from Kate Crawford: https://tinyurl.com/yax2v2vr
Pramit Choudhary
@pramitchoudhary
Welcome @dipanjanS
Pramit Choudhary
@pramitchoudhary
@aikramer2 will it be possible to check the permission on travis once? I am not able to add a branch for build
Pramit Choudhary
@pramitchoudhary
@aikramer2 was able to get rid of the exception and get the builds back up. Thanks for pointing out the fix
Ben Van Dyke
@benvandyke
Hey @pramitchoudhary @aikramer2 Partial dependence plots helped me out this morning. Thanks!
Ben Van Dyke
@benvandyke
Any thoughts on getting spark compatibility? Maybe a similar treatment to the deployed api?
Pramit Choudhary
@pramitchoudhary
Hey @benvandyke, glad it was helpful. We had thought about it, we definitely need to in-corporate Spark compatibility. Just added a new ticket: datascienceinc/Skater#203. Possible to add some more details, you think we should consider.
Pramit Choudhary
@pramitchoudhary
@benvandyke will you have the bandwidth to explore the possibility of taking up this feature ?
Ben Van Dyke
@benvandyke
@pramitchoudhary I'll think about it some more, going to write the spark partial dependence manually and perhaps that can become the base for an actual feature
Pramit Choudhary
@pramitchoudhary
@benvandyke thats a great idea :), that will enable us to make it more performant with robust scalability. Lets capture our thoughts in the ticket datascienceinc/Skater#203 as we go along. Thanks for look into it
datadave
@datadave
FYI Pramit and I recently watched https://www.ted.com/talks/cathy_o_neil_the_era_of_blind_faith_in_big_data_must_end/transcript and Pramit and Cathy have a skype at some point in the near future to get her input on model interpretation and skater.
Pramit Choudhary
@pramitchoudhary
Thanks @datadave. Her book titled “Weapons of Math Destruction” is pretty nice. I have been reading that. Would recommend to others as well. https://weaponsofmathdestructionbook.com/author/mathbabe/
Pramit Choudhary
@pramitchoudhary
Hi Everyone,
hopefully, soon we will be adding the support for building interpretable models as well within Skater. Will keep you guys updated on the progress
Pramit Choudhary
@pramitchoudhary
@Brett777 where you able to make any progress with the h20 models?
Pramit Choudhary
@pramitchoudhary
@/all
Welcoming @christophM to the group. If i have to describe him in a word, I would say he is "awesome"
Checkout his R implementation on the idea of MI here https://github.com/christophM/iml
Pramit Choudhary
@pramitchoudhary
Pramit Choudhary
@pramitchoudhary
@/all Hey guys, we have a new beta release of Skater with the ability to build interpretable models using rules extraction(Bayesian Rule List).
Steps to get started:
Quick summary to install conda and setup the python environment(recommended steps for using python3.x)

1. wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
2. bash miniconda.sh -b -p $HOME/miniconda
3. export PATH="$HOME/miniconda/bin:$PATH"
4. conda config --set always_yes yes --set changeps1 no
5. conda info -a

Installation:
Option1:
1. conda install gxx_linux-64
2. git clone the repo
3. sudo python setup.py install --ostype=linux-ubuntu --rl=True

Option2:
1. conda install gxx_linux-64
2. sudo pip install -U --no-deps --force-reinstall --install-option="--rl=True" skater==1.1.0b1
The docs are pending an update. Should be able to get to it over the weekend.
Pramit Choudhary
@pramitchoudhary
More exciting stuff to follow
Pramit Choudhary
@pramitchoudhary
Image and text interpretability coming soon to Skater