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.