Raúl Peralta Lozada

The newest chapter of Think Linear Algebra is up now!

It is about least squares regression, QR decomposition, and orthogonality:

allendowney.github.io/ThinkLinearA...

🎉 The program for this year's Causal Data Science Meeting (#CDSM2025) is now live!
📅 Nov 12–13, 2025 | 💻 Online | 🎟️ Free registration

Join us for two days of talks and debates at the intersection of causality, data science, and AI.
👉 causalscience.org

🎥 The Wednesday conference talks are now live! ✨ Watch them now on our YouTube channel: www.youtube.com/@EuroPythonC...

YouTube video by Patrick Kidger Automated ML-guided lead optimization: surpassing human-level performance at protein engineering

🚀 New talk!

"Automated ML-guided lead optimization: surpassing human-level performance at protein engineering"

▶️ www.youtube.com/watch?v=mEhB...

✨🧪 This was a talk I gave at the recent AIxBIO conference in Cambridge UK. A 10-minute pitch for what we do at Cradle!

Release 0.6.2 · skrub-data/skrub New features The DataOp.skb.full_report() now displays the time each node took to evaluate. #1596 by Jérôme Dockès. The User guide has been reworked and expanded. Changes and deprecations Ken em...

⚡ Release 0.6.2 is out ⚡

github.com/skrub-data/s...

Whoa—my book is up for pre-order!

𝐌𝐨𝐝𝐞𝐥 𝐭𝐨 𝐌𝐞𝐚𝐧𝐢𝐧𝐠: 𝐇𝐨𝐰 𝐭𝐨 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭 𝐒𝐭𝐚𝐭 & 𝐌𝐋 𝐌𝐨𝐝𝐞𝐥𝐬 𝐢𝐧 #Rstats 𝐚𝐧𝐝 #PyData

The book presents an ultra-simple and powerful workflow to make sense of ± any model you fit

The web version will stay free forever and my proceeds go to charity.

tinyurl.com/4fk56fc8

A nice primer on normalizing flows by PyMC/PyTensor devs Ricardo and Jesse. pytensor.readthedocs.io/en/latest/ga...

PyMC people: Is there a way to implement a weighted formulation of a discrete count likelihood like the poisson, discrete weibull, etc? In Stan I'd typically do this via something like

for(n in 1:N)
target += ({function}(args...) * weights[n]);

Excited to see this irl. #econsky #rstats

Many Hard Leetcode Problems are Easy Constraint Problems Use the right tool for the job.

Next up, this week's newsletter was about software interview questions! More precisely, how many of them are utterly trivialized by a half-decent constraint solver. buttondown.com/hillelwayne/...

Splines, B-splines, P-splines, and a disapproving kitten – Notes from a data witch No, I do not care about splines. But I am trying to learn about GAMLSS regression, and yes, it is to this dark place that this topic has taken me

At the risk of stretching the imagination beyond the limits of human endurance, the reader is asked to pretend that the author is interested in splines #rstats

MNT Mark cython extensions as free-threaded compatible by lesteve · Pull Request #31342 · scikit-learn/scikit-learn Part of #30007 Cython 3.1 has been released on May 8 2025. Following scipy PR scipy/scipy#22658 to use -Xfreethreading_compatible=True cython argument if cython >= 3.1 This cleans up the lock-fi...

scikit-learn 1.8 will be the first scikit-learn release with native extensions that are officially marked as free-threading compatible.

github.com/scikit-learn...

GitHub - arcruz0/marginaleffectsJAX: A JAX Backend for `marginaleffects` A JAX Backend for `marginaleffects`. Contribute to arcruz0/marginaleffectsJAX development by creating an account on GitHub.

Also in the works, but every prediction and aggregation function needs to be written manually from scratch, so it's a big project. On big datasets, it can be crazy fast. see benchmarks. github.com/arcruz0/marg...

Demo of pd.col

✨🐼 Pandas 3.0 will have `pd.col` syntax

💡 You can use it for clean chaining in `assign` and `loc`

🚀 It's happening, the PR just got merged!

Our didactic review on machine learning for causal inference, now open access:
• identifiability (theory of when the data can answer a causal question)
• machine-learning estimators
• study design (asking well-framed questions + loopholes, eg with timewise data)
www.annualreviews.org/content/jour...

Simulation-Based Inference: A Practical Guide A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers a principled framewo...

Looky Looky! 😍🥳👏
arxiv.org/abs/2508.12939
Super fun project, I ❤️ed coauthoring w/ @sbi-devs.bsky.social.
Great lead by @deismic.bsky.social & @janboelts.bsky.social. Contribs by many talented people @jakhmack.bsky.social. 🙏 to #BenjaminKurtMiller for the kickstart! @helmholtzai.bsky.social

[Online] A Tutorial for Getting Started with PyMC, Tue, Aug 12, 2025, 12:00 PM | Meetup This one-hour tutorial introduces new users to version 5 of PyMC, a powerful Python, open source library for probabilistic programming and Bayesian statistical modeling. Pa

In about an hour, I will be presenting an introductory talk on PyMC for new users. I try to address common problems and introduce the library in a non-technical way (pictures > equations). Feel free to join!

www.meetup.com/data-umbrell...

Reproducibility is a major underpinning of the scientific method. In scientific computing, this also includes the ability to reproduce your dependencies. Yet... Ruben Arts & Wolf Vollprecht - Reproducible Science Made Easy: Package Management with Pixi

Dive into our SciPy 2025 talk on Pixi Build now! Watch here: www.youtube.com/watch?v=Uey...

Reminder that all three books I've co-authored are freely available online for non-commercial use (and the fourth will be, too)

Preface I. Tensor Basics: 1. Tensors and their subparts 2. Indexing and reshaping tensors 3. Tensor operations II. Tucker Decomposition: 4. Tucker decomposition 5. Tucker tensor structure 6. Tucker algorithms 7. Tucker approximation error 8. Tensor train decomposition III. CP Decomposition: 9. Canonical polyacidic (CP) decomposition 10. Kruskal tensor structure 11. CP alternating least squares (CP-ALS) optimization 12. CP gradient-based optimization (CP-OPT) 13. CP nonlinear least squares (CP-NLS) optimization 14. CP algorithms for incomplete or scarce data 15. Generalized CP (GCP) decomposition 16. CP tensor rank and special topics IV. Closing Observations: 17. Closing observations V. Review Materials: A. Numerical linear algebra B. Optimization principles and methods C. Some statistics and probability Bibliography Index.

Tamara Kolda has a new book out: "Tensor Decompositions for Data Science:" www.mathsci.ai/post/tensor-.... Looks cool! There's a free pdf at the link.

ToC (abbreviated).

#statsky #mathsky

learning a new api? `mo.inspect()` your objects in
@marimo.io. no more dir() / help()-ing around `<object at 0x...>`...

Logic for Programmers The mathematics that will help you in your everyday programming.

I am delighted to announce the v0.11 release of Logic for Programmers! The changelog is ENORMOUS: complete rewrites of databases, decision tables, contracts, and an *entirely new chapter* on proving code correct! Over 20% more content than v0.10, so check it out today!

leanpub.com/logic/

Announcing The Irrational Decision A book about how we gave computers the power to decide for us

What’s The Irrational Decision about? Read about it here.

Screenshot of embedding atlas showing the embedding view on the left, a table at the bottom and charts on the right.

🚀 We've just open-sourced Embedding Atlas – a tool for exploring large embedding spaces through rich, interactive visualizations 📊.

GitHub - patrick-kidger/typst_pyimage: Typst extension, adding support for generating figures using inline Python code Typst extension, adding support for generating figures using inline Python code - patrick-kidger/typst_pyimage

✨v0.1 release of typst_pyimage!✨

Do you:
- write scientific papers in Typst (boo hiss LaTeX)?
- have many matplotlib figures?

Would you like the code for those images inlined directly into your Typst file, and autogenerated when you compile it?🔥

github.com/patrick-kidg...

🍎🧪🎢🧬 Any excuse to share this masterpiece: Mustached Bats Vs The Doppler Effect

Congratulations Tom!

YouTube video by 3Blue1Brown But how do AI videos actually work? | Guest video by @WelchLabsVideo

New video on the details of diffusion models: youtu.be/iv-5mZ_9CPY

Produced by Welch Labs, this is the first in a short series of 3b1b this summer. I enjoyed providing editorial feedback throughout the last several months, and couldn't be happier with the result.

We've released 4 new chapters of Applied Machine Learning for Tabular Data.

Includes: Bayesian optimization, feature selection, model comparisons, classification metrics, calibration, #rstats computing sections, and more

blog.aml4td.org/posts/2025-0...

⚡ Release 0.6.0 is now out! ⚡

🚀 Major update! Skrub DataOps, various improvements for the TableReport, new tools for applying transformers to the columns, and a new robust transformer for numerical features are only some of the features included in this release.

Announcing Toad - a universal UI for agentic coding in the terminal I’m a little salty that neither Anthropic nor Google reached out to me before they released their terminal-based AI coding agents.

The Toad is out of the bag! 🛍🐸

Announcing Toad - a universal UI for agentic coding in the terminal

willmcgugan.github.io/announcing-t...

#Python #AI