Railways of Australia.
#rayshader adventures, an #rstats tale
| pronouns | she/her |
| website | https://sevvandi.netlify.app |
| github | https://github.com/sevvandi |
| scholar | https://scholar.google.com/citations?user=XIC1yhMAAAAJ&hl=en |
Railways of Australia.
#rayshader adventures, an #rstats tale
... and now the proof of the Newton identity
\[ s_{n,k}(x) s_{n,k+2}(x) \leq s_{n,k+1}(x)^2 \]
is formalized! (If one is interested, one can find the proof at https://github.com/teorth/symmetric_project/blob/master/SymmetricProject/newton.lean .)
Copilot showed an uncanny ability to anticipate some of the steps of the proof, perhaps because it "knew" about the standard proof of this identity which I was following somewhat closely. The process is now faster than it was before, though again there was an unexpected speedbump. The standard proof of the Newton identity proceeds by reduction to the case \(k=0, n=2\), which turned out to be straightforward. What was unexpectedly tedious was the verification of the "base case"
\[ s_{0,0}(x) s_{0,2}(x) \leq s_{0,1}(x)^2 \]
which expands after a "routine" unpacking of the definitions to the AM-GM inequality
\[ x_1 x_2 \leq (\frac{x_1+x_2}{2})^2. \]
Somewhat annoyingly, I had to perform this unpacking in fine detail, for instance by tediously verifying that the 1-element subsets of {0,1} were {0} and {1}. Possibly I was missing out on some of Lean's automated tools for this (perhaps by making some trivial little lemmas to feed into Lean's simplifier). In any case, it is done. Next step is to establish Maclaurin's inequality, which I anticipate to be a quick corollary of the Newton identity.
I had the pleasure of giving a keynote at the NHS-R/NHS.pycom 2023 conference this week and talked about building open source software in both #rstats and #Python.
If you're interested in learning more (and want to dive into #overviewR and #overviewpy - the packages that make your exploratory data analysis easier!) - here are my slides: https://bit.ly/talk-building-bridges
📣 [Community Call] R in Government
With Luíza Andrade, Karly Harker, Ahmadou Dicko @dickoa and Pablo Tiscornia @pablote
🕓 Tuesday, 31 October 2023 16:00 UTC -
We invite you to learn about the challenges and lessons learned from our panelists and attendees in their efforts to make their government data, processes, and analyses more open and reproducible.
📌 More info + join the event here: https://ropensci.org/commcalls/oct2023-government/
In this community call, our panelists will share their experiences and examples of projects with R at different levels of government and in different countries. We invite you to learn about the challenges and lessons learned from our panelists and attendees in their efforts to make their government data, processes, and analyses more open and reproducible. See below for speaker bios and resources.
Stephen Fry ‘Shocked’ to Discover #AI Stole His Voice From ‘Harry Potter’ Audiobooks and Replicated It Without Consent, Says His Agents ‘Went Ballistic'
(a human stole his voice but ya know...)
https://variety.com/2023/film/news/stephen-fry-ai-stole-voice-harry-potter-audiobooks-1235727795/
Moving to a smaller instance. A re-#introduction.
I research #MachineLearning for Scientific Discovery. #ml4science #ai4science
I advocate for #OpenSource and #OpenScience when possible. A lot of my effort goes to solving problems in #LifeScience #Genomics and #RadioAstronomy.
Read our book on Mathematics for Machine Learning at https://mml-book.com
I cook to relax.