What We’re Clicking - May Link Roundup

Below you can find this month’s roundup of articles and posts shared by Cakti that drew the most attention on Twitter. The list covers coding for matrix factorization algorithms in Python, designing apps that optimize for sequential dual screen usage, preventing technical debt, and understanding the complexities and limitations involved in building apps for low-income American families.

Finding Similar Music Using Matrix Factorization

A step-by-step guide to calculating related music artists with matrix factorization algorithms. This tutorial is written in Python using Pandas and SciPy for calculations and D3.js for interactive data visualization.

Windows on the Web

Completing a task across multiple devices is a common habit. And yet, according to the author of this piece Karen McGrane, this practice is rarely considered in user design scenarios. In this article, McGrane contemplates how to design the best user experience for sequential dual screen usage.

Technical Debt 101

This article is a detailed explanation of technical debt and the negative consequences of sacrificing code quality.

What I Learned from Building an App for Low-Income Americans

Ciara Byrne’s thoughtful article on lessons learned from her experience building an app for low-income Americans. Byrne reflects not only on the challenges involved in designing for this particular community of users but also the complex definitions of low-income that must be taken into account when approaching similar projects.

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