Best practices for writing good, clean JavaScript code

Robert Martin’s book Clean Code has been on my to-read list for months now. Browsing the web, I stumbled across this repository of where Ryan McDermott applied the book’s principles to JavaScript. Basically, he made a guide to producing readable, reusable, and refactorable software code in JavaScript. Although Ryan’s good and bad code examples are written in…

How to Speak – MIT lecture by Patrick Winston

Patrick Winston was a professor of Artificial Intelligence at MIT. Having taught with great enthusiasm for over 50 years, he passed away past June. As a speaker [Patrick] always had his audience in the palm of his hand. He put a tremendous amount of work into his lectures, and yet managed to make them feel…

How to Read Scientific Papers

Cover image via wikihow.com/Read-a-Scientific-Paper Reddit is a treasure trove of random stuff. However, every now and then, in the better groups, quite valuable topics pop up. Here’s one I came across on r/statistics: Particularly the advice by grandzooby seemed worth a like, and he linked to several useful resources which I’ve summarized for you below….

7 Reasons You Should Use Dot Graphs, by Maarten Lambrechts

In my data visualization courses, I often refer to the hierarchy of visual encoding proposed by Cleveland and McGill. In their 1984 paper, Cleveland and McGill proposed the table below, demonstrating to what extent different visual encodings of data allow readers of data visualizations to accurately assess differences between data values. Since then, this table…

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…

Overviews of Graph Classification and Network Clustering methods

Thanks to Sebastian Raschka I am able to share this great GitHub overview page of relevant graph classification techniques, and the scientific papers behind them. The overview divides the algorithms into four groups: Factorization Spectral and Statistical Fingerprints Deep Learning Graph Kernels Moreover, the overview contains links to similar collections on community detection, classification/regression trees and gradient boosting papers…

17 Principles of (Unix) Software Design

I came across this 1999-2003 e-book by Eric Raymond, on the Art of Unix Programming. It contains several relevant overviews of the basic principles behind the Unix philosophy, which are probably useful for anybody working in hardware, software, or other algoritmic design. First up, is a great list of 17 design rules, explained in more…

Data Visualization Style Guide Repositories

Amy Cesal put together (1) this great overview of style guides for data visualization practice. Moreover, in the original tweet, Amy refers to other great repositories such as (2) this PolicyViz one and (3) this humongous one by Adele. Amy’s list includes many references to the best practices used by some of the leading data…