We provide an update on developments in the intersection of the R and the broader machine learning ecosystems. These collections of packages enable R users to leverage the latest technologies for big data analytics and deep learning in their existing workflows, and also facilitate collaboration within multidisciplinary data science teams. Topics covered include – MLflow: managing the ML lifecycle with improved dependency management and more deployment targets – TensorFlow: TF 2.0 update and probabilistic (deep) machine learning with TensorFlow Probability – Spark: latest improvements and extensions, including text processing at scale with SparkNLP
Javier is the author of "Mastering Spark with R", sparklyr, mlflow and many other R packages for deep learning and data science. He holds a double degree in Math and Software Engineer and decades of industry experience with a focus on data analysis. He currently works in RStudio and previously in Microsoft Research and SAP.