Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you’ll learn how to apply Automated Machine Learning, a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology.
Building machine learning models is an iterative and time-consuming process. Even those who know how to create these models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply Automated Machine Learning to your data right away.
- Learn how companies in different industries are benefiting from Automated Machine Learning
- Get started with Automated Machine Learning using Azure
- Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning
- Understand how data analysts, BI professionals, and developers can use Automated Machine Learning in their familiar tools and experiences
- Learn how to get started using Automated Machine Learning for use cases including classification and regression.
Table of contents
- I. Automated Machine Learning
1. Machine Learning: Overview and Best Practices
- Machine Learning: A Quick Refresher
- Best Practices for Machine Learning Projects
- An Iterative and Time-Consuming Process
- Growing Demand
2. How Automated Machine Learning Works
- What Is Automated Machine Learning?
- Automated ML
- II. Automated ML on Azure
- 3. Getting Started with Microsoft Azure Machine Learning and Automated ML
- 4. Feature Engineering and Automated Machine Learning
- 5. Deploying Automated Machine Learning Models
- 6. Classification and Regression
- III. How Enterprises Are Using Automated Machine Learning
- 7. Model Interpretability and Transparency with Automated ML
- 8. Automated ML for Developers
- 9. Automated ML for Everyone
- Title: Practical Automated Machine Learning on Azure
- Release date: September 2019
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492055594
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