👍read esp. for the "neat tricks"
— Mara Averick (@dataandme) June 4, 2018
"To purrr or not to purrr" via 😸 @MangoTheCathttps://t.co/da1lR3a5it #rstats #purrr #tidyverse pic.twitter.com/zUgEU2IWxS
👍read esp. for the "neat tricks"
— Mara Averick (@dataandme) June 4, 2018
"To purrr or not to purrr" via 😸 @MangoTheCathttps://t.co/da1lR3a5it #rstats #purrr #tidyverse pic.twitter.com/zUgEU2IWxS
New R package xplain: Providing interactive interpretations and explanations of statistical https://t.co/GxNqMFfboS #rstats #DataScience
— R-bloggers (@Rbloggers) June 4, 2018
🗺️ Just released v0.3.0 of usmap for #rstats
— Paolo Di Lorenzo (@dilorenzopl) June 4, 2018
Updated the shape files to the 2017 versions and added a few convenient features, like being able to specify the data for plotting using state names/abbreviations instead of just FIPS codes.https://t.co/pbym7nBizT pic.twitter.com/v373sC7ehN
Super excited to see that @jurafsky is posting chapters of the new edition of his NLP textbook online as he completes them- lots of new stuff on neural nets/embeddings-- highly recommended. https://t.co/VfbhaWb9pH
— Chris Bail (@chris_bail) June 3, 2018
rqdatatable: rquery Powered by data.table https://t.co/lNlHRGXEpC #rstats #DataScience
— R-bloggers (@Rbloggers) June 3, 2018
+1 to @erictleung's recommendation for #rstats skimr package (especially the mini histogram!). #cascadiarconf pic.twitter.com/YdXPDEzt0M
— Caitlin Hudon👩🏼💻 (@beeonaposy) June 3, 2018
Slides for my #cascadiarconf talk on contributing to R packages are here: https://t.co/z4QvUiNOTg
— Kara Woo (@kara_woo) June 2, 2018
✍🏼advice from @kara_woo for contributing to #rstats packages: improve documentation. Did this for the first time last week to give more dplyr::na_if examples because I could never use it on data frames that included dates 😖 #cascadiarconf https://t.co/xsVjGgwobj pic.twitter.com/fKRo4RC0fT
— Dr. Alison Hill (@apreshill) June 2, 2018
keras-applications - Reference implementations of popular deep learning models. https://t.co/q8DRCtO5nk
— Python Trending (@pythontrending) June 2, 2018
Free @utknightcenter MOOC "Data Visualization for Storytelling and Discovery", taught by @albertocairo. You'll learn how to use graphs, maps, charts, diagrams to extract meaning from large amounts of data & how to use #dataviz to tell stories https://t.co/bqX0E1k5PF pic.twitter.com/wHbiNIwDJQ
— GIJN (@gijn) June 2, 2018
Understanding NBA Foul Calls with Python by Austin Rochford - https://t.co/OzX5keU32h. This talk is a case study in using open source Python packages to analyze these reports in order to understand the relationship between game dynamics, player abilities, and foul calls.
— Python Software (@ThePSF) June 2, 2018
Great way to discover cool #rstats projects: search @dataandme's timeline for code-throughs! - @apreshill's keynote at #cascadiafconf pic.twitter.com/CkAgUSHNcN
— Caitlin Hudon👩🏼💻 (@beeonaposy) June 2, 2018