I like to give talks on a wide variety of subjects. If you'd like me to give a talk at your event, meetup, roast, or funeral, please get in touch!
Here are some talks I have given:
Data Science: A Vision of Things to Come
In which I try to predict the future of data science. This was a keynote at the 2020 Southern Data Science Conference. [slides]
Managing Junior Data Scientists in the Time of Coronavirus
I am trying to branch out and give talks that are less purely technical. (They're easier to write.) This one was at IBM Learn AI 2020. [slides]
Reproducibility as a Vehicle for Engineering Best Practices
Invited talk at the ICLR 2019 Workshop on "Reproducibility in ML". [slides]
Modern NLP for Pre-Modern Practioners
This was the opening keynote for QCon.ai 2019. It's a whirlwind tour of all the new hotness in NLP. [slides]
If Not Notebooks, Then What?
Invited talk at the AAAI 2019 "Workshop on Reproducible AI". [slides]
Writing Code for NLP Research
A tutorial at EMNLP 2019 that I gave along with two of my teammates. Due to a baggage-handlers strike at Brussels Airport (really!) it wasn't recorded. [slides]
Fizz Buzz in Tensorflow
I've given this talk several times: at WrangleConf 2016, at PyData Chicago 2016, and at ODSC West 2016. The ODSC version was the best, but I don't think there's a video of it. Here are the slides though.
How Becoming Not a Data Scientist Made Me a Better Data Scientist
Thoughts on why data scientists should care about software engineering best practices, from the 2018 Southern Data Science Conference. [slides]
I Don't Like Notebooks
From JupyterCon 2018 (really!). This talk is possibly what I'm most famous for. If you like memes this is the talk for you. [slides]
Fun with Trump Tweets
I gave this talk at the Twitter Developers Seattle meetup in late 2016, about two fun projects I did with Trump-related tweets. There's definitely not a video of this, but you can look at the slides.
The Joy of [Python 3.5-style] Type Hints
I pitched this to PyCon 2017, but it got rejected. So instead I used it as a last-minute fill in at a PyLadies Seattle meetup in January 2017. No video, but here are the slides.
How to Teach (and Learn) Data Science
I have given variations on this talk many times: at the Seattle DAML Meetup, at the CareerBuilder data science summit, and at Data Day Texas 2016. I don't think there's a video of it, but the slides are out there.
Learning Data Science Using Functional Python (aka Stupid Itertools Tricks)
This was originally supposed to be a variation on the previous talk, but it got away from me and turned into a crazy digression on lazy infinite sequences in Python. This is a pretty fun talk.
Image Posterization Using k-means Clustering (Workshop)
This was a hands-on workshop I ran for the Seattle PyLadies, wherein we implemented k-means clustering from scratch and used it to "posterize" images.
T-Shirts, Feminism, Parenting, and Data Science
A lightning talk for the "Seattle Data, Analytics, and Machine Learning" meetup. There's no video of it, but I wrote up a two part blog post (part 1 part 2)
F# for Startups
I gave the first version of this talk at the ".NET Startup" meetup group, then an improved version at the "Seattle F#" meetup group (slides)
Secrets of Fire Truck Society
What can we learn about the lives of fire trucks by studying their social networks? Given at the Ignite at Strata 2013.
I finally found the video of it, the reason I never could is because the description says the speaker is "Mick Thompson", but it's definitely me.