| Description |
1 online resource (414 pages) |
| Note |
Description based upon print version of record. |
|
Includes index. |
| Summary |
This book helps you to learn how to extract, transform, and orchestrate massive amounts of data to develop robust data pipelines. You'll perform complex machine learning tasks using advanced Azure Databricks features, and also explore model tuning, deployment, and control using Databricks functionalities such as AutoML and Delta Lake with ... |
| Contents |
Table of Contents Introduction to Azure Databricks core concepts Creating an Azure Databricks workspace Creating an ETL with Databricks Delta Lake with Databricks Introducing Delta Engine Structured Streaming Azure Databricks integration with Popular Python Libraries Databricks Runtime for Machine Learning Databricks Runtime for Deep Learning Model tuning, deployment and control Using DataBricks AutoML MLFlow on Azure Databricks Distributed Deep Learning with Horovod. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Data warehousing.
|
|
Microsoft Azure (Computing platform)
|
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Data warehousing |
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Microsoft Azure (Computing platform) |
| Other Form: |
Print version: Palacio, Alan Bernardo. Distributed data systems with Azure Databricks Birmingham : Packt Publishing, Limited, c2021 9781838647216 |
| ISBN |
9781838642693 (electronic bk.) |
|
1838642692 (electronic bk.) |
|
9781838647216 (pbk.) |
|
