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Getting Started with Machine Learning in Microsoft Fabric
Getting Started with Machine Learning in Microsoft Fabric
Microsoft Fabric brings data engineering, data science, and analytics together in one unified platform, making it easier to build and manage machine learning solutions.
With Fabric, you can: ✅ Prepare and transform data efficiently
✅ Build and train ML models using notebooks
✅ Track experiments and compare model performance
✅ Deploy models for real-world predictions
✅ Collaborate with your team in a single workspace
Machine learning isn't just about creating accurate models—it's about turning data into actionable insights that drive better decisi
Nice overview, this is a good summary for anyone just getting oriented.
One thing worth adding for people starting out: MLflow is built right into Fabric notebooks, so experiment tracking (metrics, parameters, model versions) happens automatically without extra setup, that's honestly one of the more underrated parts of the Data Science experience since a lot of people don't realize it's there until they stumble into the Experiments item in the workspace.
Also worth mentioning for anyone following this thread: the Data Science tutorials in Microsoft Learn walk through the full cycle end to end (ingest, train, track, deploy, score) using sample datasets, which is a solid next step after reading a high-level summary like this one.
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Nice overview, this is a good summary for anyone just getting oriented.
One thing worth adding for people starting out: MLflow is built right into Fabric notebooks, so experiment tracking (metrics, parameters, model versions) happens automatically without extra setup, that's honestly one of the more underrated parts of the Data Science experience since a lot of people don't realize it's there until they stumble into the Experiments item in the workspace.
Also worth mentioning for anyone following this thread: the Data Science tutorials in Microsoft Learn walk through the full cycle end to end (ingest, train, track, deploy, score) using sample datasets, which is a solid next step after reading a high-level summary like this one.
Thankyou @Prince0011 for Addressing the issue.
Hi tanziyaashaq ,
Thank you for reaching out to Microsoft Fabric Community Forum,
As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for the issue worked? or Let us know if you need any further assistance?
Regards,
Chaithanya
Thankyou @Prince0011 for Addressing the issue.
Hi @tanziyaashaq ,
Thank you for reaching out to Microsoft Fabric Community Forum,
As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for the issue worked? or Let us know if you need any further assistance?
Regards,
Chaithanya
Excellent overview! As someone transitioning into AI and Machine Learning, I found this very helpful. Microsoft Fabric's unified approach to data engineering, model development, experiment tracking, and deployment makes it an exciting platform to learn. Looking forward to exploring it further. Thank you for sharing!
