#Event – Resources used during my session “Building an Anomaly Detector System with a few or no lines of code” @MsftReactor

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My 1st session at Microsoft Reactor and it was amazing. We had engaging conversations around Machine Learning and Anomaly Detection, and as I promised here are the resources used.

Building an Anomaly Detector System with a few or no lines of code

More Information https://www.microsoftevents.com/profile/form/index.cfm?PKformID=0x8330114abcd


Source Code


Reference Links


Machine Learning.Net

Cognitive Services Anomaly Detector

Azure Machine Learning

Happy coding!

Greetings @ Toronto

El Bruno

#Azure – Azure Open DataSets, an amazing friend for Azure #ML Studio (Preview)


Time for a very interesting feature part of the Azure family: Azure Open Datasets. OK, when you read the name, you probably get 95% of the idea, however, let’s dig into the official definition (see references).

Azure Open Datasets are curated public datasets that you can use to add scenario-specific features to machine learning solutions for more accurate models. Open Datasets are in the cloud on Microsoft Azure and are integrated into Azure Machine Learning and readily available to Azure Databricks and Machine Learning Studio (classic). You can also access the datasets through APIs and use them in other products, such as Power BI and Azure Data Factory.

Datasets include public-domain data for weather, census, holidays, public safety, and location that help you train machine learning models and enrich predictive solutions. You can also share your public datasets on Azure Open Datasets.

This per-se is amazing, however this feature became useful when you start to work with the new amazing Azure Machine Learning Studio (Preview). Now in the [Assets / Datasets] section we can use:

  • Datasets from local files
  • Datasets from DataStore
  • Datasets from WebFiles
  • Datasets from the Open DataSet repository

And the last one is awesome because we can work with sample and free data like

All the datasets in the repository are optimized to be used in Machine Learning workflows. And, we have the chance to requests datasets or to submit and contribute with our own data. So Cool!

Happy coding!

Greetings @ Toronto

El Bruno