— In the News —
A $150,000 reward is up for grabs for any data scientist who can write code for facial recognition software that can pinpoint illegal catch on fishing boats
Algorithmic systems have a way of making mistakes or leading to undesired consequences. Here are five principles to help technologists deal with that.
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— Tools and Techniques —
Here's everything you need to know about Jupyter Notebooks, including what they are, how to use them, best practices, and links to some stellar examples.
The Elastic NBA Team Rankings is based on statistical modeling techniques frequently used in industry to predict things like bankruptcy, fraud or customer buying behavior. If you love statistics, R and basketball, then this post is for you.
Here's how to build a simple amortization table in pandas and model various outcomes.
If your organization has been underwhelmed by its data science investments, check out this new framework by Domino. The Data Science Maturity Model will help leaders and practitioners identify gaps and direct future investment.
— Resources —
IPython notebooks used to create Jake VanderPlas' new book, Python Data Science Handbook. Includes all text and code.
Curated collection of resources to learn Structured Query Language (SQL), including books, interactive courses, video lessons, bootcamps, articles, and reference material.
— Data Viz —
Each week for a year, Giorgia Lupi and Stefanie Posavec collected personal data, visualized it on a postcard, and then sent it, "snail mail," to the other person. This project became hugely popular, is now a book, and was recently acquired by MoMA. Here's a look at the project and the influence it's had on how people see data in their everyday lives.
Most colormaps that are included in Python plotting packages are perceptually nonuniform. That means that small changes in data values result in large changes in how the colors look. This repo includes a good look at the problem and a package to correct it.