If you know what to do, Microsoft Azure Machine Learning makes it real easy how to create a model, train it and deploy it to production. Prior to official preview following video tutorials are posted on MSDN Channel 9 and following are compilation of all in one place.
|1||Machine Learning||This short video introduces Cloud Machine Learning in Azure. This was basically an ad.|
|2||Overview of Azure ML||This provides an overview of the Azure Machine Learning Service. A browser based workbench for the data science workflow, which includes authoring, evaluating and publishing predictive models.|
|3||Provisioning Azure ML workspaces from Azure Portal||This video walkthroughs steps needed to provision an Azure Machine Learning workspace from the Azure Portal.|
|4||Getting Started with Azure ML Studio||This video introduces Azure Machine Learning Studio, a visual tour of the Azure Machine Learning studio workspaces and collaboration features.|
|5||Getting and Saving Data in Azure ML Studio||Data Access is the first step of data science workflow. Azure Machine Learning supports numerous ways to connect to your data. This video illustrates several methods of data ingress in Azure Machine Learning.|
|6||Preprocessing Data in Azure ML Studio||Data preprocessing is the next step in data science workflow and general data analysis projects. This video illustrates the commonly used modules for cleaning and transforming data in Azure Machine Learning.|
|7||Missing Value Handling and More||This video demonstrates how to conduct missing value handling, column and feature selection, and data splitting in ML studio.|
|8||Executing R scripts in Azure ML Studio||This video demonstrates how to execute R scripts inside the Azure ML Studio environment|
|9||R in Azure ML Studio||Azure Machine Learning supports R. You can bring in your existing R codes in to Azure Machine Learning and run it in the same experiment with provided learners and publish this as web service via Azure Machine Learning. This video illustrates how to incorporate your R code in ML studio.|
|10||Predictive Modelling with Azure ML studio||Azure Machine Learning features a pallets of modules to build a predictive model, including state of the art ML algorithms such as Scalable boosted decision trees, Bayesian Recommendation systems, Deep Neural Networks and Decision Jungles developed at Microsoft Research.This video walks through steps to building, scoring and evaluating a predictive model in Azure Machine Learning.|
|11||Introduction to Azure ML API Service||This video introduces Azure Machine Learning API service capabilities|
|12||Operationalizing “Hello World” with Azure ML Studio||This video illustrates how to operationalize a simple “Hello World” R-script and generate REST API using Azure Machine Learning Studio.|
|13||IPython and Azure ML||This video demonstrates creating a simple model, publishing it as an API on Azure, then testing it from an IPython Notebook|
I promise to keep the list updated. Happy Machine Learning!