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Automated Machine Learning

You're reading from  Automated Machine Learning

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781800567689
Pages 312 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Adnan Masood Adnan Masood
Profile icon Adnan Masood
LinkedIn
Adnan Masood, PhD is an artificial intelligence and machine learning researcher, visiting scholar at Stanford AI Lab, software engineer, Microsoft MVP (Most Valuable Professional), and Microsoft's regional director for artificial intelligence. As chief architect of AI and machine learning at UST Global, he collaborates with Stanford AI Lab and MIT CSAIL, and leads a team of data scientists and engineers building artificial intelligence solutions to produce business value and insights that affect a range of businesses, products, and initiatives.
See other products by Adnan Masood

Table of Contents (15) Chapters

Preface 1. Section 1: Introduction to Automated Machine Learning
2. Chapter 1: A Lap around Automated Machine Learning 3. Chapter 2: Automated Machine Learning, Algorithms, and Techniques 4. Chapter 3: Automated Machine Learning with Open Source Tools and Libraries 5. Section 2: AutoML with Cloud Platforms
6. Chapter 4: Getting Started with Azure Machine Learning 7. Chapter 5: Automated Machine Learning with Microsoft Azure 8. Chapter 6: Machine Learning with AWS 9. Chapter 7: Doing Automated Machine Learning with Amazon SageMaker Autopilot 10. Chapter 8: Machine Learning with Google Cloud Platform 11. Chapter 9: Automated Machine Learning with GCP 12. Section 3: Applied Automated Machine Learning
13. Chapter 10: AutoML in the Enterprise 14. Other Books You May Enjoy

Google Cloud AI Platform and AI Hub

A part of the larger AI Platform offering, Google Cloud AI Hub is the one-stop shop for all things AI – it even says so on the home page. AI Hub is in beta at the time of writing. However, that shouldn't stop you from trying out its amazing one-click deployment capabilities. AI Hub and AI Platform can be confusing; the difference is in how GCP frames the problem. AI Hub focuses on enterprise-grade sharing capabilities to enable private collaboration and hosting, while AI Platform is a larger ecosystem of all things AI, including notebooks, jobs, and platforms. This is not to say that these capabilities don't overlap, and the GCP marketing team will probably come up with a cohesive strategy one day – but until then, the duality continues.

The following screenshot shows the AI Hub home page. You navigate to this page by clicking the AI Hub link on the AI Platform page at https://console.cloud.google.com/ai-platform/dashboard...

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Authors (1)

Profile icon Adnan Masood
LinkedIn
Adnan Masood, PhD is an artificial intelligence and machine learning researcher, visiting scholar at Stanford AI Lab, software engineer, Microsoft MVP (Most Valuable Professional), and Microsoft's regional director for artificial intelligence. As chief architect of AI and machine learning at UST Global, he collaborates with Stanford AI Lab and MIT CSAIL, and leads a team of data scientists and engineers building artificial intelligence solutions to produce business value and insights that affect a range of businesses, products, and initiatives.
See other products by Adnan Masood

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