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Machine Learning Studio Classic Retirement: Transitioning to Azure Machine Learning in Excel

Olivia MillerOlivia Miller Oct 26, 2026 868 views

Question details

Excel users need a replacement for the retired Machine Learning Studio (classic) to continue building predictive analytics and machine-learning projects.

Machine Learning Studio Classic Retirement: Transitioning to Azure Machine Learning in Excel
Product
Excel / Azure
Device & OS
not provided
Scenario
Users seeking an individual-friendly machine learning service after the retirement of Machine Learning Studio (classic).
Observed behavior
Machine Learning Studio (classic) retired on August 31, 2024, requiring users to find and transition to a new platform for data modeling.
Before you start

Ensure you have an active Microsoft Azure account and a basic understanding of modern machine learning frameworks before migrating your legacy projects.

Solution 1Recommended

Migrate to Azure Machine Learning for Predictive Analytics

Azure Machine Learning is the official successor to the classic studio, offering advanced model training, deployment, and comprehensive framework support.

With the retirement of Machine Learning Studio (classic), Microsoft has transitioned its machine learning services entirely to Azure Machine Learning. This new platform provides robust tools for individuals and enterprise users alike to train and deploy predictive models directly from their datasets.

1
Sign up for an Azure account

Visit the official Microsoft Azure website to create an account. You can start with a free trial to explore the capabilities of Azure Machine Learning without upfront costs.

2
Create an Azure Machine Learning Workspace

Log into the Azure portal, search for 'Machine Learning' in the top search bar, and click 'Create' to set up a new workspace for your predictive analytics projects.

3
Export and connect your Excel data

Save your Excel datasets as CSV files. In your Azure Machine Learning workspace, navigate to 'Data' and upload these files as datastores to be used for model training.

4
Train models using modern frameworks

Utilize built-in tools or supported frameworks like PyTorch, TensorFlow, and scikit-learn to build, monitor, and deploy your predictive models.

Migrate to Azure Machine Learning for Predictive Analytics
Retirement Date: Machine Learning Studio (classic) officially retired on August 31, 2024. All new machine learning projects should be initiated within Azure Machine Learning.
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Prepare Your Machine Learning Data Seamlessly with WPS Office

While migrating your advanced machine learning models to Azure, you need a reliable tool for daily data preparation and analysis. WPS Office offers a lightweight, highly compatible spreadsheet application to manage and clean your datasets effortlessly before uploading them to the cloud.

Fully compatible with Microsoft Excel (.xlsx, .csv) formats required for Azure importsLightweight application with fast processing for large datasetsFamiliar user interface that requires no steep learning curveBuilt-in advanced data analysis tools to prepare datasets for predictive modeling
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Frequently Asked Questions

When did Machine Learning Studio (classic) officially retire?

Machine Learning Studio (classic) was officially retired by Microsoft on August 31, 2024. Users are now directed to use Azure Machine Learning for all their predictive analytics and data modeling needs.

Does Azure Machine Learning offer a free tier for individual Excel users?

Yes, Microsoft offers a free trial for Azure Machine Learning. This allows individual users to test out model training, deployment, and management features before committing to a paid subscription tier.

What machine learning frameworks are supported in the new Azure service?

Azure Machine Learning supports modern and widely used machine learning frameworks, including PyTorch, TensorFlow, and scikit-learn, providing much greater flexibility and power than the classic studio.