Final session of our #PyTensor Workshop is live!

Discover custom rewrites, speed up diagonal matrix inversions 80x, and see a mini-PyMC in action - one graph powering the full Bayesian workflow.

Watch here: dub.link/WRFuYtp

#PyMC #Python #ML #DataScience

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

Claude never seriously worked with numpy (e.g np.vectorize), nor did he approach high-performance computing with stuff like jax or pytensor.

Join Rob Zinkov at #PyDataAmsterdam 10th Anniversary on Sep 26, 1:20 PM for a beginner-friendly #PyMC sprint.

Learn, contribute, and connect with the community!

#PyTensor

Session 2 of our #PyTensor workshop dives into 𝐆𝐫𝐚𝐩𝐡 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧𝐬!

Learn eager vs. lazy transformations, autodiff under the hood, and Normalizing Flows.

Watch the full session here: dub.link/Ihd3Zc6

#PyMC #ML

Do you somewhere have a write-up of how that works on an example? I can't think of a reason we couldn't do the same thing in pymc with pytensor? After all, we also have the model graph in a data structure and can analyze and modify it.

#400557 readline: Fix MinGW Build
#400552 maintainers/team-list: add michaelBelsanti to cosmic team
#400551 python313Packages.{numba,pytensor}: make src reproducible
#400547 treewide: move to by-name
#400540 python312Packages.prometheus-api-client: 0.5.7 -> 0.6.0
#400539 gitu: 0.29.0 -> 0.30.3

Behind every #PyMC model is #PyTensor — a computational graph library for speed, flexibility & autodiff.

Session 1 of our PyTensor Workshop is live 🎥
👉 dub.link/pytensor-gra...

#PyMC #Python #MachineLearning

This week at @odsc.bsky.social AI West 2025, we're hosting a hands-on #PyTensor tutorial!

Learn how the computational graph library powering #PyMC makes probabilistic models scalable & efficient, supports complex inference, and drives real-world AI decisions.

See you there!

#ODSC2025

pytensor (and with it pymc) will use many of those helpers automatically using rewrites if appropriate, even if you write naive code. It doesn't always catch everything, so it is still good to know about them, but it can help beginners a lot.