Once the presentation is complete the presenter will open the questions panel and review the red flagged questions.

The presenter will then share their screen and the host will confirm that they can see it.

A host will introduce the speaker and the topic and then hand control to the main presenter.

All recordings are posted on within 48 hours.

All webinars are recorded and shortened to show only the content and questions.

We start the webinars approximately 20 minutes prior to the launch for the public in case there are questions or concerns.

You can either clone this repository with git, or download the entire content as a zip file by clicking on the 'Download ZIP' button on the right.

Finally, Andreas concludes which ML platform he prefers, and bad news to R fans, it turns out to be Sci-kit learn, but that is only personal preference.This repository contains materials that have been used in RStudio webinars. He mentions caret as well, but this does not factor in, however I still love CARET and refer to the course I did on Advanced Modelling for how to get up and running with CARET quickly.

Andreas then took us through the benefits of using Sci-kit learn compared with TidyModels and mlr.

I also showed how you can run external scripts from R. The pipeline was to read data in R and do some basic cleaning, pass the data to Python to split and model with Sci-kit Learn, do some visualisations in Python and then pass back to R. This is actually really intuitive in R and the webinar recording in the next section will show the detail of this.

The first session involved me taking the functionality of the reticulate package and how you can easily pass R and Python commands to convert the data from the respective formats.

Wednesday (20th January 2021) myself and a colleagues Andreas kicked off the first webinar of 2021 for the NHS-R Community with our look at the benefits of using reticulate for joining up R and Python.

R studio webinar