Hey all,
Lately, I’ve been thinking about a way to help people keep learning & practicing their coding skills long term; my new project, Mozilla Study Groups, are what I came up with, and I wanted to ping the Seattle community to see if people would be interested in trying this out locally.
The idea is to have a casual meetup, maybe 1-2 hours anywhere from weekly to monthly, where people can come and share skills in some guided demos of the code and packages they use in their research, ask each other questions, find out what each other are working on, and just generally have a place to come talk and learn about coding for research.
I’ve made a few assets to support this (all still works in progress, feedback very welcome):
– Study Group Handbook, a how-to guide for organizing these meetup groups: http://mozillascience.github.io/studyGroupHandbook/
– Study Group Website Kit, a forkable, quick to set up website to list events for your group: https://github.com/mozillascience/studyGroup
– Study Group Lessons, a collection of short lessons from past meetups, intended for recirculation: https://github.com/mozillascience/studyGroupLessons
The pilot in Vancouver is a big hit, check out their website: http://minisciencegirl.github.io/studyGroup/ .Sound interesting? These Study Groups work best when the community gets together to organize; if you’re interested in giving this a go, I’d be happy to help out and maybe scoot down from Vancouver to assist in getting started; let me know!
—
Best Regards,
Bill Mills
Community Manager
Mozilla Science Lab
Overheard: Mozilla Study Groups in Seattle
Comments Off on Overheard: Mozilla Study Groups in Seattle
Filed under software engineering
Unhide a toolbar in MPLD3
Did you ever want to know how to unhide the toolbar in MPLD3? Here is how: http://stackoverflow.com/questions/29976625/unhide-toolbar-in-mpld3
Comments Off on Unhide a toolbar in MPLD3
Filed under dataviz, Uncategorized
Interesting read: Why Stochastic Can Be a Dirty Word
A taxonomy of these public responses is apparent: relief (as predicted by the authors of the article) that they did nothing to give themselves cancer, skepticism about the author’s motives, doubt about the accuracy of the science, a belief that the science must be wrong because cancer cannot be random, and anguish about their cancer being deprived of meaning. The last 2 responses often appear together.
http://jamanetwork.com/article.aspx?doi=10.1001/jamaoncol.2015.0786
Comments Off on Interesting read: Why Stochastic Can Be a Dirty Word
Filed under health communication
What was I up to two year ago?
One fun thing about keeping my lab notebook in digital form with IPython Notebooks is that I can flip through my old work so easily. Did I say fun? I meant scary, and sometimes depressing. But yes, also fun.
For example, two years ago, I was working on some projects that are still not wrapped up today, and I was doing a lot of prep for the first edition of my now re-titled “machine learning for health metricians” class.
Hey that includes the answer to [a question someone just asked on stats.stackexchange](http://stats.stackexchange.com/q/149801/18291)
Comments Off on What was I up to two year ago?
Filed under machine learning
Jupyter Notebooks in GitHub
So cool:
https://github.com/blog/1995-github-jupyter-notebooks-3
https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks
I wonder what diffs look like?
Currently, not shown: https://github.com/fonnesbeck/statistical-analysis-python-tutorial/commit/17ca0cd15c1379f9adc4561042c4a31621baeef6
Is that next GitHub? It will be huge.
Comments Off on Jupyter Notebooks in GitHub
Filed under software engineering
Irreproducibile science as a communication failure
From: Abraham D. Flaxman
Sent: Thursday, May 7, 2015 4:40 PM
To: reproducible@u.washington.edu
Subject: [Reproducible] licenses and reproducibility: the scholarly communication lens
The recent discussion on reproducibility and licensing inspired me to read something historical about UW and software licensing that has been on my desk for a while. I think others on the list might find it interesting as well, so I scanned a copy for you: https://www.dropbox.com/s/79k92iwm20159of/williams_barnett_digital_ventures_2009.pdf?dl=0
I particularly like the idea that software is communication, and the university is an institute that is good at scholarly communication and at teaching. I think there is some framing here that could be valuable for reproducible research as well. Irreproducible results are, in a sense, a communication failure, and a lot of what we are talking about on this list are different ways to improve our scholarly communication.
–Abie
Comments Off on Irreproducibile science as a communication failure
Filed under science policy
Why do we call it “ridge” regression?
Asked and answered: http://stats.stackexchange.com/a/151351/18291
With a link to more detail: http://www.itl.nist.gov/div898/handbook/pri/section3/pri336.htm
Comments Off on Why do we call it “ridge” regression?
Filed under machine learning
A post on a talk on the book Epic Measures
I got my high school buddy to write a book about my boss… what could go wrong? They were at Town Hall Seattle a few weeks ago, and I think nothing did: http://townhallseattle.org/event/jeremy-smith-and-christopher-murray/
Is there a recording online somewhere?
Comments Off on A post on a talk on the book Epic Measures
Filed under global health
I like the term OneHotEncoder
Dummy variable just sounds demeaning to me. http://stats.stackexchange.com/questions/149122/treating-missing-data-in-voting-pattern-analysis/149572#149572
Comments Off on I like the term OneHotEncoder
Filed under machine learning
How did I end up reading a 30 year old book on density estimation?
Simple, I wanted to make violin plots for efficiency scores, and they shouldn’t have any density below zero. Here is a sneaky way to sneak such a figure out of Python/Seaborn: https://github.com/mwaskom/seaborn/issues/525#issuecomment-97651992
The truncation makes them look more like gyro meat than violins.
Comments Off on How did I end up reading a 30 year old book on density estimation?
Filed under dataviz
Healthy Algorithms 