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You're reading from  Mastering Azure Machine Learning

Product typeBook
Published inApr 2020
Reading LevelBeginner
PublisherPackt
ISBN-139781789807554
Edition1st Edition
Languages
C#
Tools
Azure
Concepts
Machine Learning
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Authors (2):
Christoph Körner
Christoph Körner
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Christoph Körner

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.
Read more about Christoph Körner

Kaijisse Waaijer
Kaijisse Waaijer
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Kaijisse Waaijer

Kaijisse Waaijer is an experienced technologist specializing in data platforms, machine learning, and the Internet of Things. Kaijisse currently works for Microsoft EMEA as a data platform consultant specializing in data science, machine learning, and big data. She works constantly with customers across multiple industries as their trusted tech advisor, helping them optimize their organizational data to create better outcomes and business insights that drive value using Microsoft technologies. Her true passion lies within the trading systems automation and applying deep learning and neural networks to achieve advanced levels of prediction and automation.
Read more about Kaijisse Waaijer

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Azure Machine Learning workspace

Azure Machine Learning is the newest member of the ML service family in Azure. It was initially built as an umbrella to combine all other ML services under a single workspace, and hence is also often referred to as the Azure Machine Learning workspace. Currently, it provides, combines, and abstracts many important ML infrastructure services and functionality such as tracking experiment runs and outputs, a model registry, an environment and container registry based on Conda and Docker, a dataset registry, pipelines, compute and storage infrastructure, and much more.

Besides all of the infrastructure services, it also integrates Azure Automated Machine Learning, Azure Machine Learning designer (, and a data-labeling UI in a single workspace that can share the same infrastructure resources. It is, in fact, the ML service that you are looking for if you want to do something serious. In many cases, it does all you can ask for and more. In this section...

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Mastering Azure Machine Learning
Published in: Apr 2020Publisher: PacktISBN-13: 9781789807554
© 2020 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
Christoph Körner

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.
Read more about Christoph Körner

author image
Kaijisse Waaijer

Kaijisse Waaijer is an experienced technologist specializing in data platforms, machine learning, and the Internet of Things. Kaijisse currently works for Microsoft EMEA as a data platform consultant specializing in data science, machine learning, and big data. She works constantly with customers across multiple industries as their trusted tech advisor, helping them optimize their organizational data to create better outcomes and business insights that drive value using Microsoft technologies. Her true passion lies within the trading systems automation and applying deep learning and neural networks to achieve advanced levels of prediction and automation.
Read more about Kaijisse Waaijer

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