I’ve given a few talks about programming. I think they’re pretty good. Usually I talk in a really excited way about something for about 25 minutes :).
A swiss army knife of debugging tools (Strange Loop 2016)
An overview of a bunch of Linux debugging tools you might love. I handed out zines at the end.
Learning systems programming with Rust (RustConf 2016)
Keynote at RustConf 2016. On how anyone can be a systems programmer.
How to trick a neural network (!!Con 2016)
Systems programming as a swiss army knife (PyCon 2015)
Abstract: You might think of the Linux kernel as something that only kernel developers need to know about. Not so! It turns out that understanding some basics about kernels and systems programming makes you a better developer, and you can use this knowledge when debugging your normal everyday Python programs.
PyCon, April 2015
Opening statements: PyCon 2015
In which I very excitedly welcome everyone to the conference. this was the first time I spoke in front of more than 1000 people and it was super fun.
You can be a kernel hacker! (Strange Loop 2014)
Strange Loop, September 2014
Abstract: Writing operating systems sounds like it’s only for wizards, but it turns out that operating systems are written by humans like you and me. I’m going to tell you what a kernel is and why you should care. Then we’ll talk about a few concrete ways to get started with kernel hacking, ranging from the super-easy to the terrifyingly difficult.
Spying on your programs with strace (!!Con 2014)
!!Con, May 2014
In which I am EXTREMELY EXCITED about explaining how to use strace to debug your code.
(errata: sysdig is in fact linux-only!)
Diving into Open Data with IPython Notebook & Pandas (PyCon 2014)
PyCon, April 2014
Demo of how to use IPython Notebook & Pandas to find out whether people like to cycle when it rains (spoiler: they don’t).
A Practical Introduction to IPython Notebook and Pandas
PyData NYC, November 2013
Hands-on tutorial on how to get started with IPython Notebook and pandas, using 311 calls from NYC open data as an example.