
Pragmatic AI: An Introduction to Cloud-Based Machine Learning, 1st edition
Title overview
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
Table of contents
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