Відео

Very clear, practical and useful talk. Thanks Frank.

The last article in the blog on the web-ste was on April 7, 2021. Is the project Qunteda alive?

great talk. Is there a new youtube channel? this one has only one video ua-cam.com/channels/0xc75IqmteIlp-i2vjKWFg.html

Excellent talk!

Awesome!!Thank you

Thanks to Achim and his team my assessments are nowadays entirely revolutionized. I assess more than 1000 students per semester all of them with exams produced by R exams. Achim's contribution to my (and my colleagues' professional well-being) is invaluable. We also have improved fairness and quality control of the items. With the generated data (from the corrections) we make IRT/Rasch analyses to identify easy/difficult items with potential problems. There is a before and after R exams...

To me R is confusing specially in oops area... It doesn't have a consistent oop system which makes CS student kind of hate it... Vectorization is not hated by anyone

Thank you

can you please tell how to read .h5 raster files in RStudio?

This is hilarious. I think this is incredibly important work. And the later stuff would help with even everyday r programming. The types and the lack of need for promosis. Also, the speed ups that can be achieved by compiling r doesn't sound like it will ever reach the... Very large 200x and more times. But I'm super hopeful about this after this talk. This is undoubtedly important work.

Thanks a lot David Gohel and Why R team.

Very nice tutorial. I use renv to set up separate environments for R, wonder if RCall from Julia could be configured to execute R code in those separate environments?

Thanks to everyone who joined today! Here are the materials: github.com/kyla-mcconnell/juliaR And if you're looking for some more R-content, feel welcome to join us at R-Ladies Freiburg: www.meetup.com/rladies-freiburg/

Great video. We need more of it.

Volcanoes? Warms a geologists heart...

Amazing work

Great job Corina!!! So intelligent and resourceful as always.Your presentation was very in depth and straight to the point. I am so proud of you 🎉 🎊 👏🏻 I love you sis💕

This is an interesting yet educative piece, thank you Emmanuel

It was a great presentation. Thanks

۞―P̳r̳e̳m̳i̳u̳m̳ ̳P̳r̳i̳v̳a̳t̳ ̳S̳e̳x̳―۞ ➡️➡️️ 》》 18cams.xyz 《《 -----------------^^----------------- ♠【﹄💖𝐊𝐋𝐈𝐊≔⫸LINK 💖﹃】 ♠みゃあこさん！ฅ( ̳• •̫ • ̳ฅ)ﾆｬﾝ !❤️ 在整個人類歷史上，強者，富人和具有狡猾特質的人捕食部落，氏族，城鎮，城市和鄉村中的弱者，無`'守和貧窮成員。然而，人類的生存意願迫使那些被拒絕，被剝奪或摧毀的基本需求的人們找到了一種生活方式，並繼續將其DNA融入不斷發展的人類社會。 說到食物，不要以為那些被拒絕的人只吃垃圾。相反，他們學會了在被忽視的肉類和蔬菜中尋找營養。他們學會了清潔，切塊，調味和慢燉慢燉的野菜和肉類，在食品市場上被忽略的部分家用蔬菜和肉類，並且學會了使用芳香的木煙（如山核桃，山核桃和豆科灌木 來調味食物煮的時候 1617619250

Thank you Kevin!

Thank you to the WhyR Foundation for supporting people’s inprovement worldwide!

Thank you Kevin !

Very good work! One question. If my target has 4 levels {Very bad,Bad,Good,Very Good} what i have to put in the vars , outcomename, outcometarget ? Thank you!

Congratulations Ewa Grabska! Amazing presentation of remote sensing data processing using R.

missed the stream. hi from Australia.

Nice. Thanks 🙂👍

Hello Rhodora from Iloilo Philippines

You should integrate it with mlr3... So that mlr3 has something to compete with tidymodels in text space...

53:00 I will live my life by this now and I hope Prof. Harrell has a job for me if i failed all other ones...

Thanks for the presentation, Chris. Just a quick question on authentication and permissions. How did you manage these? Within R using functions, implemented Active Directory groups permissions or was your shiny implementation an Enterprise version that comes with authentication component?

Brilliant stuff

I came here looking for how to implement a chatbot in R... any suggestions if quanteda has useful functions for NLG as well...

Super! Yes, you can use tidyverse in raster data analysis especially if you have a small raster whose pixel values can be easily extracted and saved as a dataframe. geom_polygon and geom_raster come handy. See: ua-cam.com/video/TUZdISDpQRk/v-deo.html

Amazing! Looking forward to the Quanteda-tidymodels integration. Greetings from a fellow Political Scientist who's getting started in the NLP world.

Hey all, I am putting together resources from the open source geospatial community that will help people in their geospatial journeys. Check out : www.kiranmayivadlamudi.com/post/resources

I'm a bit baffled by Prof. Frank Harrell's statement that he doesn't really trust causal inference in non-experimental/observational studies. Most questions in epidemiology and public health simply don't lend themselves to an experimental design - think for example about exposure to second hand smoke or long-term effects of nutrition. In those cases, the question under what circumstances an effect can be interpreted causally is of great importantance and warrants the attention it received in recent years (spearheaded by Judea Pearl and others). In my opinion, randomized controlled trials are "overrated" in the sense that they are the gold standard for causal inference in theory, but not in practice. Just look at a meta-analysis of randomized trials: Studies are often of poor quality, affectec by all sorts of biases and there is considerable unexplained heterogeneity. This is not to say that observational studies are not affected by biases, quite the contrary. But the statement that non-experimental studies can't be trusted to find causal effects does not represent the current consensus among epidemiologists and statisticians. For more in this topic, I really recommend the book by Miguel Hernán and James Robbins about causal inference (it's freely available). That being said, I apologize if I have misunderstood or misrepresented Frank Harrell's statments.

I'm not sure what Frank is getting at when he says that Type I error rate isn't an error rate, it's a probability of making an assertion. However, it's only the probability of making the assertion when the assertion is incorrect. Is there some definition of error I'm missing here?

Thank you for making this available! Very useful.

Excellent.

I love this conversation

very helpful. thank you david

I had no idea R had been integrated so deeply into MS products. I can only guess this will be a source of tools and work being done for enterprise Azure development for R developers. Super cool!

Don't so rude on interrupting Roger! Let's him talk! These are knowledge to us but time constraints is not!

Why R is better than Phyton for this application?

It's awesome!

The code of my presentation can be found at this repo github.com/cgq5/spatial-release .

Julia is an R-Star!

very valuable

Why was MATTER not mentioned towards the end?