Data Science JupyterLab environment and the Accelerated Data Science SDK are enhanced

The JupyterLab notebook session interface is enhanced so that the JupyterLab environment now supports: 

  • The Variable Inspector extension. 
  • The Table of Content extension.
  • Renders geojson, fasta, plotly, bokeh, and json files natively.
  • Latex is rendered in markdown cells.


The Accelerated Data Science (ADS) SDK is enhanced as follows: 

  • Performance improvements of the ADW dataset loader resulting in a significant speedup. 
  • DatasetFactory.open() with format='sql' no longer requires index_col to be specified. Additionally, the table parameter can be either a table or a sql expression in DatasetFactory.open().
  • ADS no longer instantiates an H2O cluster on behalf of the user. Instead the user needs to use import h2o to own and start their own cluster. 
  • You can now profile Dask operations in ADS, which allows you to monitor the CPU and memory consumption in your notebook session.
  • Dask version upgrade (version 2.10.1) with support for OCI Object Storage.
  • Several bugs in ADS have been fixed including the upsampling recommendation, visualizations issues for model evaluation, and so on.