ArchiGAN: Designing buildings with reinforcement learning

I’ve seen some uses of reinforcement learning and generative algorithms for architectural purposes already, like these evolving blueprints for school floorplans. However, this new application called ArchiGAN blew me away! ArchiGAN (try here) was made by Stanislas Chaillou as a Harvard master’s thesis project. The program functions in three steps: building footprint massing program repartition…

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…

Causal Random Forests, by Mark White

I stumbled accros this incredibly interesting read by Mark White, who discusses the (academic) theory behind, inner workings, and example (R) applications of causal random forests: EXPLICITLY OPTIMIZING ON CAUSAL EFFECTS VIA THE CAUSAL RANDOM FOREST: A PRACTICAL INTRODUCTION AND TUTORIAL (By Mark White) These so-called “honest” forests seem a great technique to identify opportunities…

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…

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,…

Tensorflow for R Gallery

Tensorflow is a open-source machine learning (ML) framework. It’s primarily used to build neural networks, and thus very often used to conduct so-called deep learning through multi-layered neural nets.  Although there are other ML frameworks — such as Caffe or Torch — Tensorflow is particularly famous because it was developed by researchers of Google’s Brain…

A/B Testing a New Look

This WordPress blogger I came across — let’s call him “John” for now — has a very peculiar way of testing out his looks. Using dating-apps like Tinder, John conducted A/B-tests to find out whether people would prefer him romantically with or without a beard.  Via a proper experimental setup, John found out that bearded John receives much…