Data Science Lab

• Auto ML Integration

  • There will be an option to train models with different algorithms and get the best model among them using Auto ML applications.

  • A new tab along with datasets is provided at the project level for Auto ML experimentations.

• Data Preparation Integration

  • Integrated the Data Preparation services in the DS Lab module.

  • Provided an icon in the Datasets tab to generate Data Preparations.

• PyTorch inferencing in Pipeline:

  • A Pytorch model can be trained, saved, and registered inside the Data Pipeline module.

  • The registered model can infer with the test data and get the predictions in the DS Lab model runner.

• Data Catalog Implementation

  • Displays the consolidated details of Data science projects, Notebooks, models, and Utility scripts.

  • Provided illustrative representation in UI

• Kernel Session Manager: Introduced a Kernel Restart icon on the Notebook header panel to kill the current session and create a new one.

• The Output cell height has been increased to 500px.

• Ellipsis icon for Cell Operations: Provided the cell operations inside the Ellipsis icon to enhance the UI experience.

• Timestamp for Notebook and Model lists: Provide Timestamp as a separate entity in the list to identify the last updated time from UI.

• Algorithms:

  • To remove the extra Print statements and unwanted output parameters.

  • Introduced optimized and standardized code.

• Merge and Split cells: Two or more cells get split or merged inside the DS Lab Notebook page.

• Static Update of the List: Instead of refreshing the entire list, a loader appears at the entity level to refresh it.

• Save As Operation: The Save As option has been provided in the Notebook toolbar to create a copy of the DS Notebook.

• Artifacts enhancement: Provided a Preview option in the Artifacts UI with limited rows. In case of the images, the .png file itself can be previewed.

• Data Sets Enhancement: Provided a Preview option in the UI with limited rows to preview the added data set.

• Provided an Add option inside the Notebook to directly add Data Sets and Data Sandbox files.

• Variable Explorer: Provided a variable explorer to show the name, type, length, and sample values for all variables that are created in the Notebook.

Please check out the given video on all the DS Lab features released under BDB 7.6 version for better understanding of the module updates.

DS Lab 7.6 Features Demo

Please Note: The Auto ML is an alpha release.