Skip to content

DSB #116


get funky on Friday with the bulletin! Read for example study about home advantage in soccer games without spectators in Papers & Books!

And as always, enjoy your reading.

Analytical – Pandas vs SQL, and it’s a draw! Obviously. But it’s also full of examples of very nice queries. (rcmd by reader) – Want to store a vector? Use a vector database. – Visual pattern analysis in order to identify Moiré effect in the San Pellegrino label.

Computer Science & Science – Be fluent with command line, this repository will teach you everything you need. (rcmd by reader) – Naming in computer science is difficult, exceptional naming is exceptionally difficult. (rcmd by reader) – How Google uses metadata in its search engine. And it’s more important than AI itself. (rcmd by reader)

Graphs and Visualizations – Nice introduction with beautiful visualizations of Fourier Transformation.
And here is the intro by 3Blue1Brown. (rcmd by reader) Lieberman created an art with facial recognition for an article in the New York Times magazine. (rcmd by reader) – Financial Times visual vocabulary – when to use which chart type. (rcmd by reader)

Business and Career – Nasdaq system failed because of an integer limits 😀 (rcmd by reader) – Really long thought about fintechs, the atomization they have created, and how banks should react, why they should focus on the financial health of their clients. – Revolut released an extension for browsers – Revolut Shopper – that automatically finds discounts.

Pop – Maybe you already heard about DeepL Translator from Germany, that seems better than Google Translate, but as you can try it yourself it’s still worse than a good human translator. (rcmd by reader) – Kobra is a visual programming language for machine learning – basicall Scratch for data science, ideal for beginners without greater ambition. (rcmd by reader) – Sperbank will pay convicts to label their data. (rcmd by reader)

Education – What is a chained map in Python? (rcmd by reader) – Nice comprehent intro to reinforcement learning with code. – Applications of Monte Carlo simulations with Go language.

Data & Libraries – New version of Flask is here. (rcmd by reader) – Generating syntetic data with Gaussian Mixture Model.–whats-in-your-data – DataProfiler is a Python library that is not only describing your data, but also monitors and identifies with pre-trained model sensitive data.

MLOps – Difference between good and bad data scientist. “Good DS has a deep understanding of data lineage & sourcing, and will often build these pipelines themselves. Bad DS thinks it is someone else’s job.” (rcmd by reader) – Dagster, data orchestrator, compares itself with Airflow. – Mr. Ng released a new specialization on Coursera about mlops in order to teach how to get and handle models on production.

Video & Podcast – Why AI is harder than we think. Is another winter coming?

Papers & Books – Paper about influence of specators on soccer matches. And even without fans home advantage remains. Czech article on that topic is here. (rcmd by reader) – Interactive Deep Learning book with code. Seems good on first sight. (rcmd by reader) – Guide for Python design patterns – and it’s a must read for everybody who wants to know more about code design. (rcmd by reader)

Behind the Fence – Experimental Behavior Scientist in BetterUp, USA.


Be First to Comment

Leave a Reply