Although cognitive services are great predefined models to start with, there will inevitably be the need to create your own custom models for ML. Discover which solutions Microsoft provides in this area.
- [Instructor] Okay so now that we have covered … machine learning on a more theoretical basis, … let's talk about Azure Machine Learning. … Azure ML is Microsoft's cloud-based platform … for machine learning, … it's not the only one though. … Microsoft also offers Databricks, … which is meant for more experienced data scientists. … But that one should not be the focus of the AI 900 exam. … It allows you to create machine learning models … with minimal amount of code. … All you need to do … is to drag and drop objects into canvas … link then properly and configure the settings. … That being said, you're still able to apply some sequel … or Python code if needed. … Once the models are ready, … they can be deployed as a web service or IoT endpoints. … Much like the endpoints that we have seen … on the cognitive services chapters. … Web Service endpoints can use Azure Container instances ACI, … or Azure Kubernetes Service AKS, … and IoT can use Docker containers. … But the best thing about Azure ML …
Skill Level Intermediate
1. Artificial Intelligence in Azure
3. Natural Language Processing
4. Creating Bots
5. Working with Machine Learning Solutions
Automated machine learning2m 20s
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