Machinelearning

R-Ladies Rome (English) - Interactive R, Python, and Shiny in the Browser with Quarto and Shinylive

In this session, Isabella Velásquez walks us through Quarto Live and Shinylive, powerful tools that allow us to create interactive R, Python, and Shiny applications without a server. These technologies make it easier than ever to share dynamic, engaging data science projects directly in the browser. What You’ll Learn ️ How Quarto Live brings interactive code to static documents ️ How Shinylive allows Shiny apps to run entirely in the browser ️ Practical use cases for data science, education, and collaboration This talk is ideal for data scientists, educators, and open-source enthusiasts who want to make their work more interactive and accessible. To further explore the subject, we recommend visiting the presentation of the talk : https://ivelasq.github.io/2025-02-21_r-python-shiny-in-the-browser More about the Speaker: - https://www.linkedin.com/in/ivelasq/ 0:00 R-Ladies Rome Chapter Intro 5:00 Isabella's Talk Please visit: https://rladiesrome.org

Isabella Velásquez

R-Ladies Rome(English) - Extending the data science workflow: {vetiver} and {pins}- Isabel Zimmerman

In this video, Isabel Zimmerman goes through the fundamental aspects of machine learning operations (MLOps) tasks, bridging the gap between data analysis and model deployment. While data practitioners excel in data analysis and model development, there's often a significant gap in understanding tasks beyond the conventional data science workflow. You'll explore crucial MLOps concepts, such as deploying models as API endpoints and monitoring model decay, while leveraging the powerful capabilities of the vetiver and pins packages. Material: - presentation: https://www.isabelizimm.me/talk-extending-ds-workflow-rladies/ - RStudioConf2022 talk: https://www.isabelizimm.me/talks/rstudioconf2022/ - Vetiver website: https://vetiver.rstudio.com/ 0:00 Welcome & R-Ladies Rome Chapter Introduction 0:04:45 Slido Pools 0:10:15 Talk Intro 0:10:56 Isalbel's Talk 0:47:53 Hands-on session 1:02:20 Q&A Have a look at our WebSite for more insights about our events: https://rladiesrome.quarto.pub/website/talks/

Isabel Zimmerman

J j Allaire Jupyter Notebooks + Quarto for customizable and reproducible documents, websites and

To share our results and communicate effectively in data science, we need to weave together narrative text and code to produce elegantly formatted, interactive output. Not only does it need to look great, but it needs to be reproducible, accessible, easily editable, diffable, version controlled and output in a variety of formats, such as PDF, HTML and MS Word for convenience and often compliance. Jupyter has already made so much of this possible. By combining Jupyter with the open-source publishing platform, Quarto, built on Pandoc, you can easily create the output format and the styling that you need for any situation. With Quarto, you can author documents as plain text markdown or Jupyter notebooks with scientific markdown, including equations (LaTeX support!), citations, cross references, figure panels, callouts, advanced layouts, and more. You can also engage readers by adding interactive data exploration to your documents using Jupyter Widgets, htmlwidgets for R, Observable JS, and Shiny. In this talk, we’ll discuss authoring these dynamic, computational documents with Quarto and Python that bring code, output, and prose together, leveraging integrations with both Jupyter and the Quarto VS Code extension. Whether you’re new to Jupyter or have thousands of notebooks already, we’ll walk you through using a single source document to target multiple formats - transforming a simple document into a presentation, a scientific manuscript, a website, a blog, and a book in a variety of formats including HTML, PDF and MS Word. We’ll also show how you can change themes and styling, and publish these artifacts directly from the command line to the web, so they’re immediately available online

Machinelearning

Resources tagged Machinelearning#

R-Ladies Rome (English) - Interactive R, Python, and Shiny in the Browser with Quarto and Shinylive

R-Ladies Rome(English) - Extending the data science workflow: {vetiver} and {pins}- Isabel Zimmerman

J j Allaire Jupyter Notebooks + Quarto for customizable and reproducible documents, websites and