The Mental Game of Python, by Raymond Hettinger

YouTube recommended I’d watch this recorded presentation by Raymond Hettinger at PyBay2019 last October. Quite a long presentation for what I’d normally watch, but what an eye-openers it contains! Raymond Hettinger is a Python core developer and in this video he presents 10 programming strategies in these 60 minutes, all using live examples. Some are…

An Introduction to Docker for R Users, by Colin Fay

In this awesome 8-minute read, R-progidy Colin Fay explains in laymen’s terms what Docker images, Docker containers, and Volumes are; what Rocker is; and how to set up a Docker container with an R image and run code on it: On your machine, you’re going to need two things: images, and containers. Images are the definition…

Learn Programming Project-Based: Build-Your-Own-X

Last week, this interesting reddit thread was filled with overviews for cool projects that may help you learn a programming language. The top entries are: Build Your Own X, by Dani Stefanovic Project-based Learning, by Tu Tran Projects from Scratch, by Algory L. Project-based Tutorials in C, by Robby Awesome DIY Software, by Cameron Eagans…

Tidy Machine Learning with R’s purrr and tidyr

Jared Wilber posted this great walkthrough where he codes a simple R data pipeline using purrr and tidyr to train a large variety of models and methods on the same base data, all in a non-repetitive, reproducible, clean, and thus tidy fashion. Really impressive workflow!

Artificial Stupidity – by Vincent Warmerdam @PyData 2019 London

PyData is famous for it’s great talks on machine learning topics. This 2019 London edition, Vincent Warmerdam again managed to give a super inspiring presentation. This year he covers what he dubs Artificial Stupidity™. You should definitely watch the talk, which includes some great visual aids, but here are my main takeaways: Vincent speaks of…

Helpful resources for A/B testing

Brandon Rohrer — (former) data scientist at Microsoft, iRobot, and Facebook — asked his network on Twitter and LinkedIn to share their favorite resources on A/B testing. It produced a nice list, which I summarized below. The order is somewhat arbitrary, and somewhat based on my personal appreciation of the resources. Course: A/B-testing by Google…

Putting R in Production, by Heather Nolis & Mark Sellors

It is often said that R is hard to put into production. Fortunately, there are numerous talks demonstrating the contrary. Here’s one by Heather Nolis, who productionizes R models at T-Mobile. Her teams even shares open-source version of some of their productionized Tensorflow models on github. Read more about that model here. There’s another great…

Northstar: The interactive, drag-and-drop data science platform by MIT

MIT researchers have spent years developing the new drag-and-drop analytics tools they call Northstar. Northstar is an interactive data science platform that rethinks how people interact with data. It empowers users without programming experience, background in statistics or machine learning expertise to explore and mine data through an intuitive user interface, and effortlessly build, analyze,…

Survival of the Best Fit: A webgame on AI in recruitment

Survival of the Best Fit is a webgame that simulates what happens when companies automate their recruitment and selection processes. You – playing as the CEO of a starting tech company – are asked to select your favorite candidates from a line-up, based on their resumés. As your simulated company grows, the time pressure increases,…