The power of {targets} package for reproducible data science скачать в хорошем качестве

The power of {targets} package for reproducible data science

From R/Medicine 2025 Reproducibility is a cornerstone of credible and robust data science. This talk delves into the powerful targets package showcasing how it streamlines and enhances reproducibility in data science workflows. The targets package in R provides a comprehensive framework for pipeline management, enabling efficient dependency tracking, automated pipeline execution, and clear documentation of the entire data analysis process. It ensures execution of complex pipelines in consistent and isolated environments. Combined with tools like {renv} and docker, this approach eliminates the it works on my machine problem. Through real-world examples, attendees will learn how to leverage these tools to create reproducible, scalable, and maintainable data science projects, ensuring that their analyses can be reliably replicated and shared across diverse computational environments. This workshop is designed for data scientists and analysts who are looking to enhance their ability to manage and scale up their analytical pipelines. By the end of the session, attendees will have a deeper understanding of the targets package, it’s capabilities and how to apply this package to their workflows, from exploration, to model building, to plotting and report generation. Attendees should follow the pre-workshop setup instructions found below. https://rsangole.netlify.app/talks/20... Rahul Sangole Rahul is a Sr Data Science manager at Apple where his work focuses on building scalable end-to-end data-science production solutions in R. He is interested in the areas of time-series analyses & forecasting, anomaly detection, and reproducible data science. Resources Slides: https://rsangole.github.io/2025-R-Med... Github: https://github.com/rsangole/2025-R-Me... Rahul's blog: https://rsangole.netlify.app/talks/20... R/Medicine: https://rconsortium.github.io/RMedici... R Consortium: https://www.r-consortium.org/