| | Become an expert in data storytelling with the online Master of Translational Data Analytics from Ohio State’s Translational Data Analytics Institute. This interdisciplinary program blends machine learning, user experience, data visualization, and design thinking to prepare you to uncover and present insights from data.
*Message from this week's sponsor, The Ohio State University |
| | |
| | 🔗 Note: if you don’t see links in this email, it’s also available on the web: dataelixir.com/archive/issue-585.html |
| | |
| | The better you can predict what comes next, the fewer bits you need to encode it. This interactive post shows how that simple idea connects compression, probability, entropy, and language models. This is a great post that “will probably blow your mind.”
ngrok blog | Annie Sexton |
| | |
| | How do you go from 97 million rows on a laptop to 16 billion rows in the cloud? This walkthrough shows how to use Polars to develop locally, then scale the same workflow to a distributed cluster.
Polars Blog | Thijs Nieuwdorp |
| | |
| | Word prediction works well for language, but isn't a great fit for arithmetic. But what if the language model didn’t need to learn arithmetic at all? In this post, Rob Porter builds calculators directly into transformer weights and uses them to explore where computation actually lives within a model.
Out of Distribution | Rob Porter |
| | |
| | ClickBench Playground lets you run queries against 110 different systems using the same 100-million-row dataset. It lets you compare syntax, results, and performance side by side.
Clickhouse | Alexey Milovidov |
| | |
| | This new guide from Hex breaks down what context actually means for AI analytics, from semantic models and metadata to existing analyses and business rules, and shows how to build it over time without turning it into a massive documentation project.
// sponsored |
| | |
| | | | Creativity in data visualization isn’t just about making charts look better. In this post, Nicola Rennie shows how choices around color, form, interaction, and even what you leave out can help people engage with, and remember the data.
Nicola Rennie |
| | |
| | | JupyterLite has always been appealing because you can run Python notebooks right in the browser. Now that Numba works there too, it’s much more capable, with faster numerical code and support for more of the scientific Python ecosystem.
Anutosh Bhat |
| | |
| | The authors of Python Polars: The Definitive Guide compressed their nearly 500-page book into a Polars cheatsheet. This is only two pages but it covers a lot of ground, from expressions and joins to lazy execution and streaming.
posit Open Source blog | Thijs Nieuwdorp, Jeroen Janssens |
| | |
| | | The hard part of ranking colorful birds is deciding what “colorful” actually means. This data-driven post turns that problem into a deep look at metrics, bias, diversity, and the choices that are baked into every ranking system.
Ryan Moulton |
| | |
| | | This week's issue sponsored by: | | |
|
