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DSB #113


winter is hopefully gone, friday sliding is over, but spring is here and also the DSB! I would recommend an article about color scales from Graphs and Visualizations or (not so) funny FB prevarication about their models and their effects on society.

As always, enjoy your reading.

Analytical – Several case studies from companies like Airbnb, Netflix, Lyft and others about marketing optimization. – 3D-CNN for land cover classification of satellite imagery using Python – includes code. – Win interpreter for League of Legends with Pyhon code.

Computer Science & Science in Python. (rcmd by reader) – List of multiple projects done not only in Python. Top notch resource perfect for inspiration. (rcmd by reader) – If you use pickle
format maybe you should learn how it works.

Graphs and Visualizations – Which color to use when? And when to use qualitative scale and when quantitative one. (rcmd by reader) – Facebook content differs for each group of users. This visualization shows who sees what. (rcmd by reader) – This is amazing, I really love beautiful visualizations and this one is more than that. It’s playful, interesting and contains math about wine. Couldn’t ask for more.

Business and Career – Banking as a plug-and-play service for non-financial entities. (rcmd by reader) – There is a potential of sexism and rasism by hiring technology that probably needs to be regulated. (rcmd by reader) – This article is about developers but it also applies to data scientists. These positions are expected to learn and study in their free time continuously and perpetually. And in whose interest is that?

Pop – Facebook itself knows that their models that maximize engagement increase polarization. The problem is quite complex, because if you want to be fair, you have to be allowed to lose money. Of course FB is afraid of regulations therefore they are proposing their own solution that would basically only protect them from competition – typical behaviour of monopoly. (rcmd by reader) – Hybrid work seems inevitable and Microsoft provides multiple interesting insights and visualizations on the topic. (rcmd by reader) – But there are also opinions that hybrid working is the worst option for everybody.  (rcmd by reader)

Education – What does it mean to compile a container? How does it work? (rcmd by reader) – Instrumental variables for non-economists. (rcmd by reader) – Lists of YouTube Machine Learning Channels and on the first place is sentdex, hence it’s a good list.

Data & Libraries – What is the new trend called data decentralization? (rcmd by reader) – Python library PyMDE for computing vector embeddings of items. (rcmd by reader) – Principles for proper data culture by Uber.

Video & Podcast – Eleven minutes of cute kittens, nothing more, nothing less… (rcmd by reader) – The one and only Mr. Ng generally about AI and its future. (rcmd by reader) – Course of Applied Machine Learning by
Cornell Tech

Papers & Books – Garbage collector that autonomously learns over time when to perform collections. What could go wrong? (rcmd by reader) – Paper about Minimum-Distortion Embedding implemented in PyMDE. (rcmd by reader) – Bizare article about automatic conversion of gene symbols to dates and floating-point numbers in Excel that mess-up with at least 704 published papers. (rcmd by reader)

Behind the Fence – Principal Data Scientist at HelloFresh in Chicago, USA.

Joke problem 😀

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