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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 Microsoft NNI

Microsoft Neural Network Intelligence (NNI) is an open source platform that addresses the three key areas of any automated ML life cycle – automated feature engineering, architectural search (also referred to as neural architectural search or NAS), and hyperparameter tuning (HPI). The toolkit also offers model compression features and operationalization. NNI comes with many hyperparameter tuning algorithms already built in.

A high-level architecture diagram of NNI is as follows:

Figure 3.26 – Microsoft NNI high-level architecture

NNI has several state-of-the-art hyperparameter optimization algorithms built in, and they are called tuners. The list includes TPE, Random Search, Anneal, Naive Evolution, SMAC, Metis Tuner, Batch Tuner, Grid Search, GP Tuner, Network Morphism, Hyperband, BOHB, PPO Tuner, and PBT Tuner.

The toolkit is available on GitHub to be downloaded: https://github.com/microsoft/nni. More information...

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