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Azure Data Scientist Associate Certification Guide

You're reading from  Azure Data Scientist Associate Certification Guide

Product type Book
Published in Dec 2021
Publisher Packt
ISBN-13 9781800565005
Pages 448 pages
Edition 1st Edition
Languages
Authors (2):
Andreas Botsikas Andreas Botsikas
Profile icon Andreas Botsikas
Michael Hlobil Michael Hlobil
Profile icon Michael Hlobil
View More author details

Table of Contents (17) Chapters

Preface 1. Section 1: Starting your cloud-based data science journey
2. Chapter 1: An Overview of Modern Data Science 3. Chapter 2: Deploying Azure Machine Learning Workspace Resources 4. Chapter 3: Azure Machine Learning Studio Components 5. Chapter 4: Configuring the Workspace 6. Section 2: No code data science experimentation
7. Chapter 5: Letting the Machines Do the Model Training 8. Chapter 6: Visual Model Training and Publishing 9. Section 3: Advanced data science tooling and capabilities
10. Chapter 7: The AzureML Python SDK 11. Chapter 8: Experimenting with Python Code 12. Chapter 9: Optimizing the ML Model 13. Chapter 10: Understanding Model Results 14. Chapter 11: Working with Pipelines 15. Chapter 12: Operationalizing Models with Code 16. Other Books You May Enjoy

Summary

Azure Machine Learning Studio provides a web environment where you can manage all the artifacts in your Azure Machine Learning workspace. You can view and manage your Jupyter notebooks, datasets, experiments, pipelines, models, and endpoints. You can also manage the compute resources and datastores that will be used in your experiments. Studio also offers interactive tools you can use to perform no-code data science experiments, something you will deep dive into in the next chapters of this book. The AutoML wizard is the first no-code experience that's baked into Azure ML Studio and allows you to run automated machine learning experiments. Azure Machine Learning designer is the next no-code experience and helps you graphically design pipelines and create workflows without writing code. This experience also enables low-code scenarios, where you can drop code snippets if needed. Finally, data labeling projects allow you to create, manage, and monitor tedious projects to...

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