Programming

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.

R-Ladies Rome (English) - R in Production - Hadley Wickham

In this inspiring talk, dive into the world of R in production with Hadley Wickham, Chief Scientist at Posit PBC (formerly RStudio).

Explore the challenges and best practices for deploying R solutions in real-world production environments, from effective code structuring to ensuring scalability and reliability. Whether you’re a seasoned data scientist or just beginning your journey with R, this event equips you with invaluable insights and actionable tips to drive impactful outcomes in your organization. Don’t miss out on this engaging discussion!

Material:

R-Ladies Gaborone & R-Ladies RTP (English) - Personal R Administration

R-Ladies Gaborone and R-Ladies RTP co-host E. David Aja as he demonstrates tips, tricks, tweaks, and some hacks for building data science dev environments that you won’t be afraid to come back to in a year.

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

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:

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:

Small Package, Broad Impact: How I Discovered the Ultimate New Hire Hack - posit::conf(2023)

Presented by Trang Le

Onboarding new hires can be a challenging process, but taking a problem-focused approach can make it more meaningful and rewarding. In this talk, I will share how I discovered the ultimate new hire hack by creating two small packages that gave me the confidence I needed when I started at BMS. Through building these packages, I not only learned R things like using bslib and making font files available for published dashboards, but also gained a deep understanding of my company’s internal systems and workflows, and connected with my team via lots of questions. The resulting packages are still heavily used today.

Join me to discover how small packages can have a broad impact and what hiring managers can do to help.

Package Management for Data Scientists - posit::conf(2023)

Presented by Tyler Finethy

In my talk, “Package Management for Data Scientists,” we will discuss software dependencies for R and Python and the common issues faced during package installations. I will begin with an overview of package management, highlighting its crucial role in data science. We’ll then focus on practical strategies to prevent dependency errors and address effective troubleshooting when these problems occur. Lastly, we will look towards the future, discussing potential package management improvements, focusing on reproducibility and accessibility for those new to the field.

R-Ladies Rome (English) - What’s new in the tidyverse - Isabella Velasquez

Welcome to R-Ladies Rome Chapter!

What’s new in the tidyverse - Speaker: Isabella Velasquez

In this video, Isabella will tell you about What’s new in the tidyverse, a suite of packages that’s revolutionized data wrangling, visualization, and analysis. Recently, Tidyverse has undergone some changes and updates to make it even more user-friendly and powerful. The changes to Tidyverse include new packages, updates to existing ones, and improvements in performance and functionality. Some of the most notable updates include enhancements to package dependencies, performance improvements for specific functions such as group_by(), and the addition of new packages such as ggplot2, readr and dplyr.