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Mastering Azure Machine Learning

You're reading from Mastering Azure Machine Learning Perform large-scale end-to-end advanced machine learning in the cloud with Microsoft Azure Machine Learning

Product type Paperback

Published in Apr 2020

Publisher Packt

ISBN-13 9781789807554

Length 436 pages

Edition 1st Edition

Languages

C#

Tools

Azure

Concepts

Machine Learning

Authors (2):

Christoph Körner

Kaijisse Waaijer

View More author details

Table of Contents (20) Chapters

Preface

About Mastering Azure Machine Learning

Section 1: Azure Machine Learning

1. Building an end-to-end machine learning pipeline in Azure FREE CHAPTER

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

Section 2: Experimentation and Data Preparation

In the second part of the book, the reader will learn how to load a dataset into Azure, visualize the data using two-dimensional embeddings, experiment with the data and models in a notebook environment, and preprocess the data for subsequent training.

This section comprises the following chapters:

Chapter 3, Data experimentation and visualization using Azure
Chapter 4, ETL, data preparation, and feature extraction
Chapter 5, Azure Machine Learning pipelines
Chapter 6, Advanced feature extraction with NLP

The rest of the chapter is locked

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Authors (2)

Körner

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.

See other products by Körner

Kaijisse Waaijer

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.

See other products by Kaijisse Waaijer

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