Data Elixir - Issue 448

The weird world of LLMs. Learning how DBs work under the hood. Probabilistic ML: Advanced Topics. Packaging C code for R. Tactile data viz. ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌

ISSUE 448 · August 15, 2023   Talks & Conferences Catching up on the weird world of LLMs Great talk summarizing the last few years of the world of LLM development. Covers what LLMs are, what you can use them for, what you can build on them, how they’re trained and some of the many challenges involved in using them safely, effectively and ethically. The post includes an edited transcript and slides if you prefer to read. North Bay Python | Simon Willison   Sponsored Link Applied Data Science with Python In this intermediate level course from Coursera, learn how to conduct statistical analysis, critique data visualization, apply machine learning, analyze social network connectivity, and much more. Enroll for free.       Reach Data Elixir readers by sponsoring an issue. Click here for details.   Posts & Tutorials How to Match LLM Patterns to Problems In this follow-up to his LLM Patterns post from a couple weeks ago, Eugene Yan explores potential problems when using LLMs and the patterns that help mitigate them. Covers issues related to both internal LLMs that you control and external LLMs that you don't control.  Eugene Yan   LearnDB This new Python project is a good opportunity to learn how databases work under the hood. Essentially, it's a simplified sqlite clone that's been implemented from scratch with the intention to make it easy to learn and tinker with.  GitHub | Spandan Bemby   Wrapping C Code in an R Package If you work in R and a collaborator who works in C gives you some code, what do you do? You could rewrite their code in R. You could say, "no thanks." Or, you could follow this step-by-step tutorial and package up their C code to make it available in R. Jonathan Carroll    How to fill maps with density gradients with R Plotting hundreds of data points on a small map of a city and have it make any sense is hard to do. This tutorial explores the issues and shows how to fix overplotted points on maps by creating bins or filled density gradients using R, {ggplot2}, and {sf}. Andrew Heiss   Resources Probabilistic Machine Learning: Advanced Topics Kevin Murphy's Advanced Topics book is for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty. The final version was just released and is available in print or follow the links to download a free PDF. Kevin Patrick Murphy   Tools & Code functime functime is a Python library for time-series machine learning and embeddings at scale. DescendantAI   causact The {causact} R package is bringing numpyro speed to R.  Learning computational Bayesian inference has never been easier. GitHub | Adam Fleischhacker   Outlier What a yarn! Great story about tactile data visualization - with crochet! If you like the ideas here, be sure to follow the links. Nieman Journalism Lab | Sarah Scire      How did you like this issue of Data Elixir? 👎    1     2     3     4     5   👍       Was this email forwarded to you?  Sign up here >>     Data Elixir, LLC P.O. Box 21255 Boulder, CO 80308 Data Elixir® is curated and maintained by Lon Riesberg. If you have questions or suggestions, just reply back to this email. Unsubscribe