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Great presentation

Awesome work. Thanks.

9:42

Super entertaining and informative! Thanks!

Awesome presentation.

Thank you, Joel!

Unfortunately very poor audio quality. Over the whole video, hard to stand.

Thanx for the video...help me a lot

Thank you for the great presentation and explanation!

🦀 rusty

Great presentation

Cool to see Nix stuff in Lux :)

Amazing thanks for the presentation

Great. Do you share the code for the revealjs?

Really great talk! And thank you for mentioning my book :)

Also very curious about his comments on LLMs. He's right. An LLM is not creative. And will probably never replace humans at the high level stuff.

Very interested in nanoparquet. I had the same complaint about arrow. Big package with a lot of functionality and a lot of dependencies. Would appreciate a lightweight package to read and write parquet files!

One of the most productive people in the world! He's even debugging during the interview!

This was such a great interview. Thanks for conducting this, Audrey! I always like to hear from primary sources. And here you have two of the founding members of the R community. They have such insightful comments!

Thank you so much for the introduction and for open code!

Emil, thank you, I don´t know if you would read this... but maybe someone could answer. I have a theoretical doubt, wouldn't it be better to convert to factor after having the factor type predictor variables separated in the split? that way the levels that the variable in train knows would not be informed by the levels that test knows they could take.

Thank you very much🎉

Thanks for the tutorial I am using adehabitatHR, sp and other related spatial package to calculate Home range of individual species through adehabitatHR I am able to generate the MCP and Kernel density home range of individuals. But the output of area calculation is very low e-9 I used the UTM projection for zone 45N please help me.. Even when I change the projection to WGS84 the area remains the same Can you tell me what is wrong

🎉🎉🎉🎉🎉

gracias por este video, me queda bien claro el uso de ggplot. con muchos detalles

Thanks for this! Very useful.

Podrían compartir por favor el material del taller

interested in how is this compared to a naive regression based approach?

Super video

(MRAN) website and CRAN Time Machine will be retired on July 1, 2023.

amazing tutorial - thank you all - Rahul and Ramin in particular

we want to know from the beginning . it start after some video parts passed away

it's very useful for beginners. Thanks, Rahul, so nice hands-on tutorial

Thanks for uploading this -- very useful content.

Please attache dataset here also.

Newer versions of the slides/handouts are at hbiostat.org/rmsc

Session starts at 13:20

Its very useful presentation. Thanks alot. I am looking for the heterogenous treatment effect using DML. Please let me know if you have any resources for heterogenous treatment effect estimation.

Most excellent!!

Thank you for the walk through!

1:30 Knowledge catalogs with TKCat 19:55 Linked dataframes 39:17 DuckDB All In-Process Analytical DBMS ("The SQLite for Analytics", short demo at 50:40) 58:50 Database list against the matrix: use of tax list an vegtable for the assessment of vegetable-plot data

Too much environmental.... too little ecology 🙁

thanks for yr wonderful lecture , do u mind providing the slide link?

Presentation begins at 10:21.

Is there a transcript available, somewhere? People really shouldn’t have to rely on craptions, especially for talks about accessibility… Thanks.

The code in my examples is impossible to read, here are my slides: github.com/brshallo/tidy-pairwise-operations-user2022/blob/main/3-ways-tidy-pairwise.pdf

That was a great presentation. Thanks for sharing. #tidymodels and #vetiver are both great packages that I will definitely use as part of my workflow.

Vetiver is definitely a game-changer. Congrats Julia and to all the Posit team too for creating this amazing package!!

please mentioned the twitter handle of the speakers so that we can connect as and when these talks will be held.

Tutorial slides: user2022tutorial.netlify.app/#1