Scalable Machine Learning with the Microsoft Machine Learning Server

Big data can often be more than the in-memory dataframes allow. Scalable Machine Learning with Machine Learning Server: This course will teach you how to create scalable, end-to-end machine learning experiments using R and Python, using the Microsoft Machine Learning Server. You will first learn how to process, transform, visualize, and import big data. Next, you will learn how to create custom, scalable and distributed functions that can be executed in many compute contexts. You will also learn how to use the MicrosoftML package's state-of-the-art machine learning algorithms. Next, we'll integrate machine learning experiments into SQL Server. We will then cover how to use the machine learning server using Hadoop and Spark, as well as integration with popular frameworks like SparkR, Sparklyr, and PySpark. We will create a Spark development environment using scracth and spin up an HDInsight cluster on Microsoft Azure. After completing this course, you will be able to create scalable machine learning experiments with R and Python using XDF, Hadoop Distributed File System and SQL Server.