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Automated Machine Learning

You're reading from   Automated Machine Learning Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781800567689
Length 312 pages
Edition 1st Edition
Languages
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Author (1):
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Adnan Masood Adnan Masood
Author Profile Icon Adnan Masood
Adnan Masood
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction to Automated Machine Learning
2. Chapter 1: A Lap around Automated Machine Learning FREE CHAPTER 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

Introducing automated ML in an organization

Now that you have reviewed the automated ML platforms and the open source ecosystem and understand how it works under the hood, wouldn't you like to introduce automated ML in your organization? So, how do you do it? Here are some pointers to guide you through the process.

Brace for impact

Andrew Ng is the founder and CEO of Landing AI, the former VP and chief scientist of Baidu, the co-chairman and co-founder of Coursera, the former founder and leader of Google Brain, and an adjunct professor at Stanford University. He has written extensively about AI and ML and his courses are seminal for anyone starting out with ML and deep learning. In his HBR article on AI in the enterprise, he poses five key questions to validate whether an AI project would be successful. We believe that this applies equally well to automated ML projects. The questions you should ask are as follows:

  • Does the project give you a quick win?
  • Is...
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