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Hands-On Machine Learning with Azure

You're reading from   Hands-On Machine Learning with Azure Build powerful models with cognitive machine learning and artificial intelligence

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789131956
Length 340 pages
Edition 1st Edition
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Authors (6):
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Jen Stirrup Jen Stirrup
Author Profile Icon Jen Stirrup
Jen Stirrup
Ryan Murphy Ryan Murphy
Author Profile Icon Ryan Murphy
Ryan Murphy
Anindita Basak Anindita Basak
Author Profile Icon Anindita Basak
Anindita Basak
Thomas K Abraham Thomas K Abraham
Author Profile Icon Thomas K Abraham
Thomas K Abraham
Parashar Shah Parashar Shah
Author Profile Icon Parashar Shah
Parashar Shah
Lauri Lehman Lauri Lehman
Author Profile Icon Lauri Lehman
Lauri Lehman
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Toc

Table of Contents (14) Chapters Close

Preface 1. AI Cloud Foundations FREE CHAPTER 2. Data Science Process 3. Cognitive Services 4. Bot Framework 5. Azure Machine Learning Studio 6. Scalable Computing for Data Science 7. Machine Learning Server 8. HDInsight 9. Machine Learning with Spark 10. Building Deep Learning Solutions 11. Integration with Other Azure Services 12. End-to-End Machine Learning 13. Other Books You May Enjoy

Summary

Azure Machine Learning Studio is a fully managed platform for developing machine learning models, enabling the user to concentrate on the essential tasks and problems in machine learning development. The graphical user interface is easy to learn and its usage requires no programming skills. Even users who have no prior experience in programming or machine learning can learn to use it, and the Experiment template collection contains many real-world examples of ML models to start with. ML Studio is a great way to start learning to develop ML models, and the sample datasets in ML Studio make it possible to develop your own models, even if you don't have your own data to start with.

Machine Learning Studio contains modules for all the most common ML-related tasks, such as data preprocessing, tuning hyperparameters, and evaluating the performance of ML algorithms. If the...

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