Talks¶
Here are some of the talks that I have given, (with slides/video/audio, when available)
2018¶
Terraforming Jupyter: Changing JupyterLab to suit your needs¶
JupyterCon, New York, NY. August 2018
Co-presented with Stephanie Stattel
( abstract )
Interview with Paco Nathan at JupyterCon 2018¶
JupyterCon, New York, NY. August 2018
SciPy 2018 Lightning talks¶
SciPy, Austin, TX. July 2018
co-MC with Anthony Scopatz
( video: Wednesday ) ( video: Thursday ) ( video: Friday )
2017¶
Jupyter: Kernels, Protocols, and the IPython Reference Implementation¶
JupyterCon, New York, NY. August 2017
Co-presented with Matthias Bussonnier
( abstract )
SciPy 2017 Lightning talks¶
SciPy, Austin, TX. July 2017
co-MC with Anthony Scopatz
( video: Wednesday ) ( video: Thursday ) ( video: Friday )
2016¶
2015¶
How IPython, and you can, too¶
Neustar Research, San Francisco, CA. March 2015
A command-line driven talk about all of the useful things in IPython before you even get to the notebook interface. Here’s a tweet from an attendee of that talk:
https://twitter.com/jkru/status/573972962405015552
2014¶
Putting the v in IPython: vim-ipython and ipython-vimception¶
SciPy, Austin, TX. July 2014
A talk about vim-ipython, bipython, and ipython-vimception.
2013¶
Cython - The Speed of C within the convenience of Python¶
Guest lecture in AY 250: Python Computing for Data Science, UC Berkeley, November 2013
( slides )
Whetting your appetite (capstone lecture for 3 day bootcamp)¶
Python Boot Camp, Berkeley, CA. August 2013
simple web scraper, sqlite, email, and some Flask: (Aug 28, 2013): Access files at http://www.pythonbootcamp.info/schedule
Making people do animal vocalizations: so here’s the bit where I first get the idea to make people moo (because they were typing and giving me a thumbs up would have made them stop typing). And shortly after this point is where I actually make them moo the first time. And make them meow after that.
A Portrait of One Scientist as a Graduate Student¶
SciPy, Austin, TX. June 2013
In this talk, I will focus on the how of reproducible research. I will focus on specific tools and techniques I have found invaluable in doing research in a reproducible manner. In particular, I will cover the following general topics (with specific examples in parentheses): version control and code provenance (git), code verification (test driven development, nosetests), data integrity (sha1, md5, git-annex), seed saving ( random seed retention ) distribution of datasets (mirroring, git-annex, metalinks), light-weight analysis capture ( ttyrec, ipython notebook)
( slides )
2012¶
Introduction to IPython and the IPython Notebook¶
UC Berkeley Python Bootcamp, August 20th, 2012
Development 2: Testing and Debugging (with philosophical remarks)¶
UC Berkeley Python Bootcamp, August 22nd, 2012
Matplotlib, beyond the basics¶
Astronomy 250, Python Computing for Data Science, UC Berkeley, January 2012.
Emerging victorious from the onslaught of the beginning of the semester in January 2012, including a nasty cold with a fever of 104 F, I delivered a guest lecture on matplotlib where I start off by saying how ” I’m a little doped up”, and about 25 minutes into it end up blurting out ” I’m totally high right now!” - which is awesome since it was recorded and captured for posterity.
( video )
...¶
I probably gave talks between 2008 and 2012, but can’t recall them now
...¶
2008¶
Nearest neighbor search using CUDA or how I learned to start worrying and fear the float¶
Redwood Center Lab Meeting, UC Berkeley, August 15, 2008
Kozachenko-Leonenko Entropy Estimation (with the help of GPUS)¶
Redwood Center Lab Meeting, UC Berkeley, March 7th, 2008
2007¶
Napoleon@Home - Distributed World Domination¶
Lightening Talk at SuperHappyDevHouse 20
NO MORE SOLITAIRE, MINESWEEPER, SODOKU, etc! particiapte in:
DISTRIBUTED THINKING a.k.a. HUMAN COMPUTATION
The PDF slides have working links to the projects mentioned. You can also find the links here
( slides )