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Mastering Azure Machine Learning

You're reading from   Mastering Azure Machine Learning Perform large-scale end-to-end advanced machine learning in the cloud with Microsoft Azure Machine Learning

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789807554
Length 436 pages
Edition 1st Edition
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Authors (2):
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Christoph Körner Christoph Körner
Author Profile Icon Christoph Körner
Christoph Körner
Kaijisse Waaijer Kaijisse Waaijer
Author Profile Icon Kaijisse Waaijer
Kaijisse Waaijer
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Toc

Table of Contents (20) Chapters Close

Preface Section 1: Azure Machine Learning
1. Building an end-to-end machine learning pipeline in Azure FREE CHAPTER 2. Choosing a machine learning service in Azure Section 2: Experimentation and Data Preparation
3. Data experimentation and visualization using Azure 4. ETL, data preparation, and feature extraction 5. Azure Machine Learning pipelines 6. Advanced feature extraction with NLP Section 3: Training Machine Learning Models
7. Building ML models using Azure Machine Learning 8. Training deep neural networks on Azure 9. Hyperparameter tuning and Automated Machine Learning 10. Distributed machine learning on Azure 11. Building a recommendation engine in Azure Section 4: Optimization and Deployment of Machine Learning Models
12. Deploying and operating machine learning models 13. MLOps—DevOps for machine learning 14. What's next? Index

Change is the only constant – preparing for change

When working with any of the big cloud providers, you should differentiate their offerings broadly into three types of service:

  • Infrastructure as a Service (IaaS)
  • Platform as a Service (PaaS)
  • Software as a Service (SaaS)

IaaS services are all-infrastructure abstractions such as virtual machines (compute), disks (storage), and networking; PaaS services are platforms built on top of these components with additional functionality that exposes the underlying services. SaaS services, in contrast, are just exposed through a UI and don't give you any access to the underlying data.

Azure Machine Learning is a great example of a PaaS offering, as it combines different infrastructure services, UIs, and SDKs to give you great new features and full access to the underlying services, such as blob storage, training clusters, and container registries. You will also see on your monthly Azure bill that you will...

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