R Weekly 2022-W22 RScreencasts, Deep Learning with R

This article is originally published at

Hello and welcome to this new issue!

• How to have (my) content shared by R Weekly?

This week’s release was curated by Batool Almarzouq, with help from the R Weekly team members and contributors.

Highlight

• RScreencasts.com: A collection of 80+ hours of time-stamped, annotated TidyTuesday screencasts highlighting the R packages and functions used in each section and what the activity is.

• Deep Learning with R, 2nd Edition

Insights

• Creating a Reproducible Example

• Editorial Automation: Why & How to Set Up Chat-Ops for your Own Review System on GitHub

R in the Real World

• Real house price plots

Resources

• RScreencasts.com: A collection of 80+ hours of time-stamped, annotated TidyTuesday screencasts highlighting the R packages and functions used in each section and what the activity is. Screencasts by David Robinson. Annotation by Alex Cookson and Eric Fletcher. Website by Oscar Baruffa. For more detail, read the launch post.

• A variety of visualisations and analysis in NLP & causal inference

• Deep Learning with R, 2nd Edition

• Outstanding User Interfaces with Shiny

• Create machine learning models with R and tidymodels

New Packages

???? Go Live for More New Pkgs ????

• {PINstimation} - PINstimation: A package for the estimation of models of probability of informed trading

• {klassets} - a collection of functions to simulate data sets to teach how some Statistics Models and Machine Learning algorithms works

• {ggcorset} - corset plots visualize the distribution of measurements at each time point.

CRAN

• {tidyterra} 0.1.0: Tools for {terra} objects. Plot Spat* objects {ggplot2} and manipulate them with {dplyr} and {tidyr}.

Updated Packages

• future 1.26.1 - future: Unified Parallel and Distributed Processing in R for Everyone

• {ichimoku} 1.3.1: Visualization and Tools for Ichimoku Kinko Hyo Strategies

Videos and Podcasts

• How to Get Started with the R Programming language

• gghighlight package for improved Visualization

• R Packages: Package metadata (rpkgs03 8)

• Episode 32: Consulting with Shiny Panel Discussion

• Programming Games with Shiny, Roll the Dice, RStudio

Gist & Cookbook

• A script to get all the functions from an R package and then expand to include all the arguments in a dataframe by Tom Mock

R Internationally

• Arabic, Part Three, Introduction to Part Three of R Programming Course

• Gráficos descriptivos en R

• Regression mit Bootstrapping in R

• Meetup Mayo 2022: Estadística descriptiva con R: Gráficas, tablas y medidas de resumen

• Generando tutoriales interactivos con el paquete {learner}

Tutorials

• Calling R From Python With rpy2

• Philly Center City District Sips 2022: An Interactive Map

• Introducing tidyterra

• Cool Word Clouds in R

• Real-Time Collaborative Editing on RStudio Cloud

R Project Updates

Updates from R Core:

Upcoming Events in 3 Months

Events in 3 Months:

• Fitting distributions in R (NHS workshop): June 8th

• New York R Conference: June 8th-10th

• UseR! (Online): June 20th-23rd

• Rstudio::Conf: July 25th-28th

• A list of R conferences and meetings

• This week’s local R-User and applied stats events

Call for Participation

Your support will keep R Weekly team moving! ????

Quotes of the Week

Today's shaded relief map is Malawi. #rayshader adventures, an #rstats tale pic.twitter.com/xZ5a0QaIQ8

— flotsam (@researchremora) May 24, 2022

This used to be me when I was first learning linear regression. ????

But here's what's changed for me.#rstats #datascience pic.twitter.com/eMWU2XMROn

— Matt Dancho (Business Science) (@mdancho84) May 24, 2022

Thanks for visiting r-craft.org
This article is originally published at
Please visit source website for post related comments.