In this video, learn why and how to track assets and code you’re creating in an end to end machine learning workflow.

Time Index:

  • [01:20] How to track assets and artifacts
  • [04:20] Demo – How to keep track of code
  • [05:58] Why it’s important to manage datasets + Demo

For More Info:

In this video, learn how you can use Azure Event Grid and Azure Machine Learning to trigger and consume machine learnings events. We talk about why eventing is important and how you can enable scenarios such as run failure alerts and retraining models.

Jump To:

  • [00:50] What is Event Grid?
  • [01:32] Why is this useful?
  • [02:32] Demo – How to set up an event subscription
  • [03:40] Demo – How to filter events
  • [05:30] Demo – Logic app example

Links:

In part 2 of a 3 part series, focused on the Bot Framework, this episode looks at how you can use the telemetry capture capabilities built into the Bot Framework to analyze your bots usage and gain actionable insights by exploring data such as user / conversation trends, channel breakdown and dialog completion vs abandonment.

We discuss why bot analytics are crucial, take a look at how easy it is to enable telemetry capture within your bot and how to drill into your data using Azure and Power BI.

Index

  • [00:40] – Discussion about why bot analytics are important
  • [02:15] – Demo showing how telemetry is wired up within a .NET Core sample bot
  • [04:40] – Viewing telemetry captured during a debug session within Visual Studio
  • [06:40] – Analyzing your telemetry within Application Insights in Azure and creating a dashboard
  • [10:20] – Open source Power BI dashboard for advanced bot analytics

For More Info:

This is the final, part 4 of a four-part series that breaks up a talk that Seth Juarez gave at the Toronto AI Meetup.

Part 1, Part 2 and Part 3 were all about the foundations of machine learning, optimization, models, and even machine learning in the cloud.

In this video Seth shows an actual machine learning problem (see the GitHub repo for the code) that does the important job of distinguishing between tacos and burritos.

The primary concepts included is MLOps both on the machine learning side as well as the deliver side in Azure Machine Learning and Azure DevOps respectively.

This is Part 3 of a four-part series that breaks up a talk that Seth Juarez gave at the Toronto AI Meetup.

Parts 1 and 2  introduce basic machine learning concepts as well as specific models using TensorFlow respectively.

In this video he goes more in depth into an example of a common data science process, how convolutions work in convolutional neural networks, and finally how this can be done in the cloud using Azure Machine Learning.

In this episode of CodeStories: France meet some of the developer relations team, Christopher, Maud, and Olivier, and local developer community leaders at the Microsoft office and the Ignite Tour stop to learn about what they’re doing in developer communities across France and how they’re helping people get skilled on Azure.

Visual Studio Code offers many great features for Data Scientists and Python developers alike, allowing you to explore and experiment on your data using the flexibility of Jupyter Notebooks combined with the power and productivity of VS Code. Tune in to learn how to supercharge your Jupyter Notebooks with VS Code.

Learn More:

In this episode of CodeStories, Seth Juarez joins local Cloud Advocate, Christopher Maneu, on a tour of the Microsoft office in Paris, his remote office,  and a scuba diving club.

Learn how Christopher has automated a logbook with IoT Retrofitting https://aka.ms/CodeStories/compressor.

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