Training ImageNet with R
This post explores how to train large datasets with TensorFlow and R. Specifically, we present how to download and repartition ImageNet, followed by training ImageNet across multiple GPUs in distributed...continue reading.
Author: Javier Luraschi
pins 0.4: Versioning
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...continue reading.
sparklyr 1.1: Foundations, Books, Lakes and Barriers
Today we are excited to share that sparklyr 1.1 is now available on CRAN! In a nutshell, you can use sparklyr to scale datasets across computing clusters running Apache Spark....continue reading.
sparklyr 1.0: Apache Arrow, XGBoost, Broom and TFRecords
With much excitement built over the past three years, we are thrilled to share that sparklyr 1.0 is now available on CRAN! The sparklyr package provides an R interface to...continue reading.
sparklyr 0.9
Today we are excited to share that a new release of sparklyr is available on CRAN! This 0.9 release enables you to: Create Spark structured streams to process real time...continue reading.
