In this episode we'll cover a quick overview of new capabilities in Azure Machine Learning like the Visual Interface for drag-n-drop machine learning and the Automated Machine Learning UI as well as our MLOps approach to productionalize machine learning from training to deployment. We'll also quickly highlight how to prepare your data using our new integration with Azure Data Factory and even visualize results of model predictions via our integration with Power BI. Learn More: Try it today for free AML OverviewTry out sample Azure Machine Learning Jupyter notebooksLearn more about MLOps [00:40]- Data preparation via integration with Azure Data Factory[01:53] – Finding new data to improve your model training with Azure Open DataSets[03:00] – Drag n drop machine learning via the Visual Interface[04:10] – New Azure Machine Learning Studio UI[05:45] – Automated Machine Learning in hosted Jupyter Notebook[09:40] – Automated Machine Learning in Azure Machine Learning Studio UI[10:20] – Dataset profiling and exploration in Azure Machine Learning Studio UI[11:11] – Tensorflow deep learning model training in hosted Jupyter Notebook[13:54] – Tensorboard integration[14:20] – Automated hyperparameter sweep via Azure Machine Learning Hyperdrive [14:48] – Easily deploying models to test & production environments with Azure DevOps integration[16:45] – Integrating deployed ML models into Power BI The AI Show's Favorite links: Don't miss new episodes, subscribe to the AI Show Create a Free account (Azure) AI Blog Fast ML MIT News | AI Medium | Francesca Lazzeri Deep Learning vs. Machine Learning Get Started with Machine Learning