Christoph Scheuch

@christophscheuch.bsky.social

Making finance and economics research more transparent and reproducible | Data Editor @ Society for Financial Studies · Researcher @ HU Berlin · Co-creator of tidy-finance.org & econdataverse.org

Can LLMs teach you everything about AI? In theory, yes. In practice, it’s overwhelming. That’s why @niccrane.bsky.social and I built a course for @athlyticz.bsky.social. It cuts the noise and gives a clear workflow using R across ML and LLMs, from sports to beyond. athlyticz.com/llm

SynergiZing ML & LLMs in R | tidymodels + RAG Course

Learn production R workflows blending tidymodels with LLMs — tool-calling, RAG with ragnar, Shiny deployment, and vitals evaluation.

athlyticz.com

it never ceases to amaze me that I can refer to duckdb functions in R expressions as though they were R functions and everything gets translated to SQL

dplyr code with duckdb functions in all caps

tbl_files <- tbl(db, "csvs") |>
  # CAPS for duckdb functions
  mutate(
    # $speaker has directory names with the patterns:
    # - `[speaker]-[listener]` (listener specific data)
    # - `[speaker]` (default version)
    # so compute appropriate $speaker, $listener values
    dir_parts = speaker |> STRING_SPLIT("-"),
    speaker = dir_parts |> LIST_FIRST(),
    listener = dir_parts |> LIST_LAST(),
    listener = ifelse(listener == speaker, "default", listener)
  ) |>
  select(speaker, listener, file, label, logprob, model_name, model_commit)

Last week I posted about using structured output in {ellmer} to turn text into data, but a friend pointed out that the LLM had mixed up the words "conscious" and "consciousness" in its summary. So how can we fix that? 🧵(1/3) #rstats #llms #ai

Looking forward to my first pure #Python conference ever at PyData Berlin 🐍 If you are interested in getting to know Shinylive and WebAssembly in Python, feel free to join my talk tomorrow at noon titled „Building Reactive Data Apps with Shinylive and WebAssembly“ ✌️

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Another new CRAN release with @tealemery.bsky.social 💪 {datacommons} is a wrapper for the Google Data Commons API v2, which provides unified access to global public stats in a knowledge graph, thus reducing data-wrangling pain. Feedback as always very welcome 🙏 github.com/tidy-intelli...

GitHub - tidy-intelligence/r-datacommons: Client for the Google Data Commons API V2

Client for the Google Data Commons API V2. Contribute to tidy-intelligence/r-datacommons development by creating an account on GitHub.

github.com

New #RStats package on CRAN: {imfweo} (w/ @tealemery.bsky.social) gives easy access to IMF’s World Economic Outlook. It's part of the #EconDataverse, helping economists + financial professionals work with sovereign-level data. Feedback welcome ✌️ github.com/Teal-Insight...

GitHub - Teal-Insights/r-imfweo: Seamless Access to IMF World Economic Outlook (WEO) Data

Seamless Access to IMF World Economic Outlook (WEO) Data - Teal-Insights/r-imfweo

github.com

#rstats has anyone added a new provider to ellmer? I see that it’s doable but I’m hoping to see if someone has blazed that trail for me and I can follow in their footsteps steps.