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…

R Image Art, by Michael Freeman

Michael Freeman — information researcher at the University of Washington — was asked whether he could manipulate images with only R programming and he thought to give it a try. In his blog, Michael demonstrates how he used ggplot2 and the imager packages, among others, to go from this original photo: To this dot representation: And this…

Computers decode what humans see: Generating images from brain activity

I recently got pointed towards a 2017 paper on bioRxiv that blew my mind: three researchers at the Computational Neuroscience Laboratories at Kyoto, Japan, demonstrate how they trained a deep neural network to decode human functional magnetic resonance imaging (fMRI) patterns and then generate the stimulus images. In simple words, the scholars used sophisticated machine learning to…

Generating Pusheen with AI

Zack Nado wrote the best machine learning application I’ve seen so far: a neural network architecture that generates new Pusheen pictures. In his blog, Zack describes his generative adversarial network (GAN) , a special type of machine learning architecture where two neural networks try to fool each other. Zack first gave the discriminator network some real Pusheen images,…

Super Resolution: Increasing image quality CSI-like

Super-resolution imaging is a class of techniques that enhance the resolution of an imaging system (Wikipedia). The entertainment series CSI has been ridiculed for relying on exaggerated and unrealistic applications of it: Until recently, such upscaling of images were though near impossible. However, we have evidenced some pretty amazing breakthroughs in the deep learning space recently. Artificial Intelligence can think ahead, learn physics, and…

Datasets to practice and learn Programming, Machine Learning, and Data Science

Many requests have come in regarding “training datasets” – to practice programming. Fortunately, the internet is full of open-source datasets! I compiled a selected list of datasets and repositories below. If you have any additions, please comment or contact me! For information on programming languages or algorithms, visit the overviews for R, Python, SQL, or Data Science,…

Generating 3D Faces from 2D Photographs

Aaron Jackson, Adrian Bulat, Vasileios Argyriou and Georgios Tzimiropoulos of the Computer Vision Laboratory of the University of Nottingham built a neural network that generates a full 3D image of a single portrait photograph. They turn a photograph like this… … into an accurately creepy 3D image like this. You can try it with your own…

t-SNE, the Ultimate Drum Machine and more

This blog explains t-Distributed Stochastic Neighbor Embedding (t-SNE) by a story of programmers joining forces with musicians to create the ultimate drum machine (if you are here just for the fun, you may start playing right away). Kyle McDonald, Manny Tan, and Yotam Mann experienced difficulties in pinpointing to what extent sounds are similar (ding, dong)…