Azure Machine Learning Pipelines | AI Show

Posted on Posted in aft-ai, AI

This video talks about Azure Machine Learning Pipelines, the end-to-end job orchestrator optimized for machine learning workloads. With Azure ML Pipelines, all the steps involved in the data scientist’s lifecycle can be stitched together in a single pipeline improving inner-loop agility, collaboration, and reuse of data and code, while maintaining high reliability.  Learn More:  Azure […]

No Code Deployment and Enriched Model Registry with AML Service | AI Show

Posted on Posted in aft-ai, AI

We’ll be discussing updates to the Azure Machine learning service model registry to provide more insights about your model. Also, learn how you can deploy your models easily without going through the effort of creating additional driver and configuration files. Learn More:  Learn more about Azure Machine Learning service Try out sample machine learning notebooks […]

Machine Learning Interpretability Toolkit | AI Show

Posted on Posted in AI, Artificial Intelligence, Machine Learning

Understanding what your AI models are doing is super important both from a functional as well as ethical aspects. In this episode we will discuss what it means to develop AI in a transparent way. Mehrnoosh introduces an awesome interpretability toolkit which enables you to use different state-of-the-art interpretability methods to explain your models decisions. By using […]

Machine Learning Models | AI Show

Posted on Posted in AI

Machine Learning is sometimes confusing. From the esoteric terms to elevated expositions it seems like a terribly difficult area to get into. Since I started as a developer I totally get the mismatch! In this episode we tackle the one term that is used all of the time in Machine Learning: the elusive "model." First […]

Anomaly Detector v1.0 Best Practices | AI Show

Posted on Posted in AI

In our last two episodes we learned a bit about the Azure Anomaly Detector service. We first learned a bit about what it is and how it can be used. Then we looked into bringing the service on premises using containers. As with any service of this kind sometimes it takes a little tweaking to […]