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Distributed Data Systems with Azure Databricks

You're reading from  Distributed Data Systems with Azure Databricks

Product type Book
Published in May 2021
Publisher Packt
ISBN-13 9781838647216
Pages 414 pages
Edition 1st Edition
Languages
Author (1):
Alan Bernardo Palacio Alan Bernardo Palacio
Profile icon Alan Bernardo Palacio

Table of Contents (17) Chapters

Preface Section 1: Introducing Databricks
Chapter 1: Introduction to Azure Databricks Chapter 2: Creating an Azure Databricks Workspace Section 2: Data Pipelines with Databricks
Chapter 3: Creating ETL Operations with Azure Databricks Chapter 4: Delta Lake with Azure Databricks Chapter 5: Introducing Delta Engine Chapter 6: Introducing Structured Streaming Section 3: Machine and Deep Learning with Databricks
Chapter 7: Using Python Libraries in Azure Databricks Chapter 8: Databricks Runtime for Machine Learning Chapter 9: Databricks Runtime for Deep Learning Chapter 10: Model Tracking and Tuning in Azure Databricks Chapter 11: Managing and Serving Models with MLflow and MLeap Chapter 12: Distributed Deep Learning in Azure Databricks Other Books You May Enjoy

Section 3: Machine and Deep Learning with Databricks

This section explores concepts around the use of machine learning and deep learning models. At the end of this section, you will be able to create, train, and deploy predictive models harnessing the power of distributed computing.

This section contains the following chapters:

  • Chapter 7, Using Python Libraries in Azure Databricks
  • Chapter 8, Databricks Runtime for Machine Learning
  • Chapter 9, Databricks Runtime for Deep Learning
  • Chapter 10, Model Tracking and Tuning in Azure Databricks
  • Chapter 11, Managing and Serving Models with MLflow and MLeap
  • Chapter 12, Distributed Deep Learning in Azure Databricks
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Distributed Data Systems with Azure Databricks
Published in: May 2021 Publisher: Packt ISBN-13: 9781838647216
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