Pragmatic AI: An Introduction to Cloud-Based Machine Learning, 1st edition

Published by Addison-Wesley Professional (August 22, 2018) © 2019

  • Noah Gift

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Pragmatic AI is the first truly practical guide to solving real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Writing for students who aren’t professional data scientists, Noah Gift demystifies all the tools and technologies you need to get results. He illuminates powerful off-the-shelf cloud-based solutions from Google, Amazon, and Microsoft, as well as accessible techniques using Python. Throughout, readers find simple, clear, and effective working solutions that show them how to apply machine learning, AI and cloud computing together in virtually any organization, creating solutions that deliver results, and offer virtually unlimited scalability.

  • Illuminates the latest solutions from Google, Amazon, and Microsoft, plus powerful techniques based on Python and R
  • Real-world examples and workflows show how machine learning, AI, and cloud computing come together in real business solutions
  • Covers every step from deployment to production, focusing on cloud environments that maximise scalability and simplify deployment
  • Addresses coding, libraries, statistical techniques, modeling for fast prototyping, and more

Foreword

Preface

Acknowledgments

About the Author

 

Part I: Introduction to Pragmatic AI

Chapter 1: Introduction to Pragmatic AI

Chapter 2: AI and ML Toolchain

Chapter 3: Spartan AI Lifecycle

 

Part II: AI in the Cloud

Chapter 4: Cloud AI Development with Google Cloud Platform

Chapter 5: Cloud Ai Development with Amazon Web Services

 

Part III: Creating Practical AI Applications from Scratch

Chapter 6: Predicting Social-Media Influence in the NBA

Chapter 7: Creating an Intelligent Slackbot on AWS

Chapter 8: Finding Project Management Insights from a Github Organization

Chapter 9: Dynamically Optimizing EC2 Instances on AWS

Chapter 10: Real Estate

Chapter 11: Production AI for User Generated Content (UGC)

 

Appendix A: AI Accelerators

Appendix B: Deciding on Cluster Size

 

Index
Noah Gift is lecturer and consultant at UC Davis Graduate School of Management in the MSBA program. Professionally, Noah has approximately 20 years’ experience programming in Python and is a member of the Python Software Foundation. He has worked for a variety of companies in roles ranging from CTO, general manager, consulting CTO, and cloud architect. Currently, he is consulting start-ups and other companies on machine learning and cloud architecture, and is doing CTO-level consulting via Noah Gift Consulting. He has published close to 100 technical publications including two books on subjects ranging from cloud machine learning to DevOps. He is also a certified AWS Solutions Architect. Noah has an MBA from University of California, Davis; an MS in computer information systems from California State University, Los Angeles; and a BS in nutritional science from Cal Poly, San Luis Obispo. You can find more about Noah by following him on Github (https://github.com/noahgift/), visiting http://noahgift.com, or connecting with him on https://www.linkedin.com/in/noahgift/.

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