Section 1: Azure Machine Learning
by Christoph Korner,
Kaijisse Waaijer
Mastering Azure Machine Learning
- Preface
- Section 1: Azure Machine Learning
- 1. Building an end-to-end machine learning pipeline in Azure
- 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
In the first part of the book, the reader will come to understand the steps and requirements of an end-to-end machine learning pipeline and will be introduced to the different Azure Machine Learning. The reader will learn how to choose a machine learning service for a specific machine learning task.
This section comprises the following chapters:
- Chapter 1, Building an end-to-end machine learning pipeline in Azure
- Chapter 2, Choosing a machine learning service in Azure
-
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