This session will provide an introduction to machine learning concepts and to show how you can analyze data to create code to determine whether or not someone is likely to leave a tip. We are going to review the data preparation steps required prior to machine learning, then show how you can implement the solution in Python. This is meant to be an introductory session, and you will see how you can run the code yourself in Azure so that you can get started with Machine Learning.
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Kevin (@kekline) serves as Principal Program Manager at SentryOne. He is a founder and former president of PASS and the author of popular IT books like SQL in a Nutshell. Kevin is a renowned database expert, software industry veteran, Microsoft SQL Server MVP, and long-time blogger at blogs.sentryone.com/author/kevinkline. As a noted leader in the SQL Server community, Kevin blogs about Microsoft Data Platform features and best practices, SQL Server trends, and professional development for data professionals.
Ginger is the principal consultant at Desert Isle Group specializing in Data Analytics. As a Microsoft MVP in Data Platform and a Microsoft Certified Trainer, she is proficient in creating solutions using the entire Microsoft Data Stack, the Azure Data Stack including Power BI, Databricks, Data Factory, Data Lake Gen 2, Data Analytics, Synapse and Machine Learning with Python. Ginger also enjoys sharing technology by teaching certification courses at Interface, as instructor at Datacamp as well as many different community tech events. Ginger has written a Azure Machine Learning book and is currently working on another book on AI. When not working, she maintains her blog http://www.desertislesql.com and spends time on Twitter @desertislesql.