Javier is the author of “Mastering Spark with R”, pins, sparklyr, mlflow and torch. He holds a double degree in Math and Software Engineer and decades of industry experience with a focus on data analysis. Javier is currently working on a project of his own; and previously worked in RStudio, Microsoft Research and SAP.
August 23, 2021
A new release of pins is available on CRAN today. This release adds support to time travel across dataset versions, which improves collaboration and protects your code from breaking when remote resources change unexpectedly.
January 21, 2021
Last year, pins got released as a brand new R package to pin, discover and cache remote resources for R users.
February 4, 2020
Open source code is an essential piece in making science reproducible. Tools like 'rmarkdown' and GitHub facilitate running and sharing outcomes with colleagues and with the broad scientific community
November 28, 2019
New CRAN release for pins adds support for cloud boards (Azure, Google Cloud and S3), new functions, use cases and many other improvements.
January 25, 2019
This talk introduces new features in sparklyr that enable real-time data processing, brand new modeling extensions and significant performance improvements.
August 23, 2017
sparklyr facilitates a connection between R and Spark using a full-fledged dplyr backend with support for the entirety of Spark’s MLlib library.
August 17, 2017
sparklyr facilitates a connection between R and Spark using a full-fledged dplyr backend with support for the entirety of Spark’s MLlib library.
