This video provides an introduction to using Spark machine learning in a Scala notebook within IBM Data Science Experience. Find more videos in the Spark Learning Center at and Data Science Experience Learning Center at .
Copyright 2017 IBM Corporation. All rights reserved. IBM, the IBM logo, Cognos, the Cognos logo and other IBM products and services are trademarks of International Business Machines Corporation in the United States, other countries, or both. Excel, Internet Explorer, PowerPoint, SharePoint and Windows are registered trademarks of Microsoft Corporation. Mozilla, the Mozilla logo, Firefox and the Firefox logo are registered trademarks of Mozilla Corporation. Other company, product or service names may be trademarks or service marks of others. iPad® and Apple® are registered trademarks of Apple Inc. The information contained in this video is provided for informational purposes only, and is provided AS IS without warranty of any kind, express or implied. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, these materials. Nothing contained in these materials is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software. References in these materials to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or capabilities referenced in these materials may change at any time at IBM’s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way. Sample data is used in this video to develop sample applications of the IBM Program. These records may contain fictional data manually or machine generated, or factual data compiled from academic or public sources, or data used with permission of the copyright holder. These fictitious records include sample data for sales transactions, product distribution, finance, and human resources. Any resemblance to actual names, addresses, contact numbers, or transaction values is coincidental. Other sample files may contain fictional data manually or machine generated, factual data compiled from academic or public sources, or data used with permission of the copyright holder, for use as sample data to develop sample applications. Product names referenced may be the trademarks of their respective owners. Unauthorized duplication is prohibited.