Many developers still treat #python as another programming language. But there are now many hints that we are witnessing a new phenomenon, a new mode of interacting with computers. Not as general but more widely accessible.
Evidence the huge popularity of #jupyter notebooks which are among the most downloaded visual studio code extensions.
Sometimes people say Python is the new excel but thats not quite capturing it. Its more the extension of #linux sysadmin scripting to include #datascience
R version of Python package survivalist, for model-agnostic survival analysis
https://thierrymoudiki.github.io/blog/2026/02/09/r/python/survivalist-r-package
This week, I had a wonderful experience when returning to R. After several years of writing Python as a Machine Learning Engineer (and occasionally dabbling in Julia), The Tidyverse ecosystem in R astounded me with how short and expressive the functional style of programming was for analysing and visualising data. I first used R in an undergraduate statistics course (which was not a subject I enjoyed at the time). In the 11 years that passed, I went through mathematical neuroscience and ended up in the field of machine learning and data science — where Python reigns supreme, especially for neural networks.
We are entering the era of the Entropy Trap. 🌀
As AI homogenizes our data, we risk a mass extinction of high-fidelity human information. I’ve written about how synthetic noise is dissolving the structural integrity of our digital world and how we can fight back.
Read the full essay: https://medium.com/@makalin/the-entropy-trap-the-architecture-of-digital-erosion-3f762353ca89
I also dive into my latest project CarbonCheck, a low-level utility designed to filter this digital decay at the source 👇
https://github.com/makalin/CarbonCheck
Optimizing k-NN search – Making Vector Search Faster with Batched Early Abort
Ask me anytime about David Ross and his 21 distinctive qualities of net art. I was at that lecture in 1999. Oh, and #EpsteinFiles and all that. Fuck, maybe I am in there? Not. We (being artists who were pro #Zapatistas or #datascience #bigdata artists) were kind of ignored by #hedgefund and #presentationlayer types in the 1990s. We were also right about most things, if you look at what we were writing at the time. Anyway David, come over here to #mastodon and discuss?
https://www.theguardian.com/commentisfree/2026/feb/13/gender-studies-trump-epstein
Neural architecture search revolutionizes machine learning by automating model design. Discover how NAS algorithms like DARTS and evolutionary methods discover optimal architectures faster than manual design, reducing search time from thousands of GPU days to just hours while achieving superior performance. #MachineLearning #DeepLearning #ArtificialIntelligence #MLOps #DataScience #NeuralNetworks
In today’s AI driven world, analytics platforms are only as good as their data. With the ever-increasing amount of data being collected in various applications, databases, and data warehouses in an enterprise, managing and ingesting data into a central platform for purposes of analytics and AI is a cumbersome and costly process. Databases and data … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/mirroring-for-sql-server-in-microsoft-fabric-generally-available/" class="more-link">Continue reading<span class="screen-reader-text"> “Mirroring for SQL Server in Microsoft Fabric (Generally Available)”</span></a>
Performant Data Reductions with #Perl
Video of a talk I delivered remotely at the London Perl and #Raku Workshop in 2024
#commandline #datascience #openmp
https://www.youtube.com/watch?v=u_CkgLTeR4g
Open Risk
The ML Engineer
Andrii Kuznietsov
The R Data Scientist
Mehmet Turgay AKALIN
1337 $#!+ I did that
MUDASSAR SALEEM
Alberto Morillo
Christos Argyropoulos