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Azure Machine Learning studio web experience is generally available

Published date: 08 July, 2020

The Azure Machine Learning studio web experience is now generally available and bringing new features:

  • Notebooks: IntelliSense, checkpoints, tabs, editing without compute, updated file operations, improved kernel reliability and more. 

  • Experimentation:   

    • Charts: Edit and add new charts, Display scatter or line plots etc.  

    • Displaying the minimum, maximum and last logged metric value of runs tabularly.  

  • Compute: Improvements in provisioning latency, user experience and actionable error/warning messages.  

  • Data labelling:  Create, manage and monitor labelling projects directly inside the studio web experience. The machine learning assisted labelling feature (Preview) lets you trigger automatic machine learning models to accelerate the labelling task 

    • Image Classification Multi-class and Image Classification Multi-label for projects  

    • Object identification (Bounding Box)  

  • Fairlearn (preview):  Integrated in Azure Machine Learning to store and track models fairness (disparity) insights in Azure Machine Learning studio and easily share their models’ fairness learnings among different stakeholders.  

  • Designer (preview):  

    • Graph engine, with new-style modules, asset library, output settings. 

    • Modules:  

      • Computer vision: Support image dataset preprocessing, and train PyTorch models (ResNet/DenseNet), and score for image classification  

      • Recommendation: Support wide and deep recommender 

As a result of these updates, some assets will be removed from the Azure portal UI and will only be available in Azure Machine Learning studio, such as Experiments, Pipelines, Models and Deployments (now called “Real-time endpoints”).

To learn more, please refer to Azure Machine Learning documentation.

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  • Azure Machine Learning
  • Features

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