staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

JoaoLages

Maybe you've heard about this technique but you haven't completely understood it, especially the PPO part. This explanation might help.

We will focus on text-to-text language models 📝, such as GPT-3, BLOOM, and T5. Models like BERT, which are encoder-only, are not addressed.

Reinforcement Learning from Human Feedback (RLHF) has been successfully applied in ChatGPT, hence its major increase in popularity. 📈

RLHF is especially useful in two scenarios 🌟:

• You can’t create a good loss function
  • Example: how do you calculate a metric to measure if the model’s output was funny?
• You want to train with production data, but you can’t easily label your production data

cboettig

# My preferred defaults (may be changed in individual chunks)
opts_chunk$set(tidy=FALSE, warning=FALSE, message=FALSE, cache=TRUE, 
               comment=NA, verbose=TRUE, fig.width=6, fig.height=4)

# Name the cache path and fig.path based on filename...
opts_chunk$set(fig.path = paste("figure/",
                                gsub(".Rmd", "", knitr:::knit_concord$get('infile')),
                                "-", sep=""),
               cache.path = paste(gsub(".Rmd", "", knitr:::knit_concord$get('infile') ), 
                                "/", sep=""))

zross

• Eurostat, World Bank and others: https://ikashnitsky.github.io/2017/data-acquisition-two/
• Star Wars data: in dplyr, http://dplyr.tidyverse.org/reference/starwars.html
• Baby names data: babynames package, https://cran.r-project.org/web/packages/babynames/index.html
• Movies data: https://cran.r-project.org/web/packages/ggplot2movies/index.html ggplot2movies package
• Game of Thrones screen time: https://github.com/Preetish/GoT_screen_time
• Open Bike Data: https://github.com/ropensci/bikedata
• Tons of data through 538: https://cran.r-project.org/web/packages/fivethirtyeight/vignettes/fivethirtyeight.html
• Public health data England: fingertipsR, https://cran.r-project.org/web/packages/fingertipsR/
• Financial data via Quandl: https://www.quandl.com/tools/r
• Cyclones: https://github.com/ropensci/rrricanesdat

MarkEdmondson1234

## GUIDE TO AUTH2 Authentication in R Shiny (or other online apps)
## 
## Mark Edmondson 2015-02-16 - @HoloMarkeD | http://markedmondson.me
##
## v 0.1
##
##
## Go to the Google API console and activate the APIs you need. https://code.google.com/apis/console/?pli=1
## Get your client ID, and client secret for use below, and put in the URL of your app in the redirect URIs
##  e.g. I put in https://mark.shinyapps.io/ga-effect/ for the GA Effect app, 

oliyoung

[core]
	excludesfile = ~/.gitignore_global
	pager = diff-so-fancy | less --tabs=4 -RFX

[difftool "sourcetree"]
	cmd = opendiff \"$LOCAL\" \"$REMOTE\"
	path =

[alias]
    aa = add --all