We are delighted to announce the rstudio::conf schedule! Expect four days of amazing speakers, workshops, and events.
In this post, we walk through the tools and functionality we used to automate survey results reporting.
gt 0.6.0 includes new features that will make your display/summary tables look and work better.
We are thrilled to announce the release of vetiver, a framework for MLOps tasks in R and Python. Use vetiver to version, share, deploy, and monitor a trained model.
Jo Ann Stadtmueller from Data Society describes the growing challenges faced by the financial services industry and the critical role that data science plays in finding accurate, flexible solutions.
RStudio Academy is a new training program for professional data science teams. In this post, we explore the pillars that make Academy a tailored and effective experience for data scientists.
We are so happy to announce the release of pins for Python. You can use pins to publish, version, and share objects such as datasets and models.
Welcome to the RStudio Community Monthly Events Roundup! In this post, we update you on upcoming events happening at RStudio and share how to find the great presentations and talks from last month.
We are excited to announce our partnership with Microsoft Azure ML. You can use RStudio Workbench in conjunction with Azure to build machine learning models at scale.
The Designing the Data Science Classroom workshop at rstudio::conf will equip educators with concrete information on content, workflows, and infrastructure for teaching data science.
We are excited to announce the MEAP release of the second edition of Deep Learning with R. This book is a hands-on guide to deep learning using Keras and R.
We are excited to announce real-time collaborative editing on RStudio Cloud. Users can join the same project, edit code, and immediately see each other’s changes.
In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This third post focuses on features that save you time and trouble.
Many tools used routinely by software developers can also be useful to data scientists.