Machine Learning for Business

Using Amazon SageMaker and Jupyter

• Éditeur: Manning
• Année: 2019
• ISBN:
  9781638353973
• Sujet: Ciencia de la computación
• Sous-sujet: Redes neuronales

Summary

• Imagine predicting which customers are thinking about switching to a competitor or flagging potential process failures before they happen
• Think about the benefits of forecasting tedious business processes and back-office tasks
• Envision quickly gauging customer sentiment from social media content (even large volumes of it).
• Consider the competitive advantage of making decisions when you know the most likely future events

Machine learning can deliver these and other advantages to your business, and it's never been easier to get started!Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Machine learning can deliver huge benefits for everyday business tasks. With some guidance, you can get those big wins yourself without complex math or highly paid consultants! If you can crunch numbers in Excel, you can use modern ML services to efficiently direct marketing dollars, identify and keep your best customers, and optimize back office processes. This book shows you how. About the book Machine Learning for Business teaches business-oriented machine learning techniques you can do yourself. Concentrating on practical topics like customer retention, forecasting, and back office processes, you'll work through six projects that help you form an ML-for-business mindset. To guarantee your success, you'll use the Amazon SageMaker ML service, which makes it a snap to turn your questions into results. What's inside

• Identifying tasks suited to machine learning
• Automating back office processes
• Using open source and cloud-based tools
• Relevant case studies

About the reader For technically inclined business professionals or business application developers. About the author Doug Hudgeon and Richard Nichol specialize in maximizing the value of business data through AI and machine learning for companies of any size. Table of Contents: PART 1 MACHINE LEARNING FOR BUSINESS1 ¦ How machine learning applies to your businessPART 2 SIX SCENARIOS: MACHINE LEARNING FOR BUSINESS2 ¦ Should you send a purchase order to a technical approver?3 ¦ Should you call a customer because they are at risk of churning?4 ¦ Should an incident be escalated to your support team?5 ¦ Should you question an invoice sent by a supplier?6 ¦ Forecasting your company's monthly power usage7 ¦ Improving your company's monthly power usage forecastPART 3 MOVING MACHINE LEARNING INTO PRODUCTION8 ¦ Serving predictions over the web9 ¦ Case studies

Table des matières

• Copyright
• Brief Table of Contents
• Table of Contents
• Preface
• Acknowledgments
• About this book
• About the Author
• About the cover illustration
• Part 1. Machine learning for business
• Part 2. Six scenarios: Machine learning for business
• Part 3. Moving machine learning into production
• Appendix A. Signing up for Amazon AWS
• Appendix B. Setting up and using S3 to store files
• Appendix C. Setting up and using AWS SageMaker to build a machine learning system
• Appendix D. Shutting it all down
• Appendix E. Installing Python
• Index
• List of Figures
• List of Tables
• List of Listings