How to Accelerate the End-to-End Machine Learning Lifecycle on Azure

This Azure ML session is for all who want to know how to: - create code-free ML models (using AutoML as well as the drag & drop pipeline creation method) - create ML models using Python (created either in Azure Notebooks or locally) - directly use pre-built ML models under Azure Cognitive APIs We will also cover the end-to-end ML life cycle; how to train ML models, how ML models can be versioned and deployed for inference, and we can use them as part of other DevOps, data warehousing or ETL pipelines. [ev