Intro to Azure Machine Learning: Predict Who Survives the Titanic
Interested in doing machine learning in the cloud? In this demo-heavy talk, I will set the stage with some information on the different types of machine learning (clustering, classification, regression, and anomaly detection) supported by Azure Machine Learning and when to use each. Then, for the majority of the session, I’ll demonstrate using Azure Machine Learning to build a model which predicts survival of individuals on the Titanic (one of the challenges on the Kaggle website). I’ll talk through how I analyze the given data and why I choose to drop or modify certain data, so you will see the entire process from data cleaning to building, training, testing, and deploying a model. You’ll leave with practical knowledge on how to get started and build your own predictive models using Azure Machine Learning.
Speaker - Jennifer Marsman
Jennifer Marsman is a Principal Software Development Engineer in Microsoft’s Developer and Platform Evangelism group, where she educates developers on Microsoft’s new technologies. In this role, Jennifer is a frequent speaker at software development conferences around the world. In 2016, Jennifer was recognized as one of the “top 100 most influential individuals in artificial intelligence and machine learning” by Onalytica. She has been featured in Bloomberg for her work using EEG and machine learning to perform lie detection. In 2009, Jennifer was chosen as “Techie whose innovation will have the biggest impact” by X-OLOGY for her work with GiveCamps, a weekend-long event where developers code for charity. She has also received many honors from Microsoft, including the “Best in Role” award for Technical Evangelism, Central Region Top Contributor Award, Heartland District Top Contributor Award, DPE Community Evangelist Award, CPE Champion Award, MSUS Diversity & Inclusion Award, Gold Club, and Platinum Club. Prior to becoming a Developer Evangelist, Jennifer was a software developer in Microsoft’s Natural Interactive Services division. In this role, she earned two patents for her work in search and data mining algorithms. Jennifer has also held positions with Ford Motor Company, National Instruments, and Soar Technology. Jennifer holds a Bachelor’s Degree in Computer Engineering and Master’s Degree in Computer Science and Engineering from the University of Michigan in Ann Arbor. Her graduate work specialized in artificial intelligence and computational theory. Jennifer blogs at http://blogs.msdn.com/jennifer and tweets at http://twitter.com/jennifermarsman.