Deep learning cookbook : Practical recipes to get started quickly

By:

Osinga, Douwe

Language: ENG Publication details: Navi Mumbai 2018Edition: 1stDescription: xv, 234p. | Binding - Paperback | 22.8*17.8 cmISBN:

9789352137572

Subject(s):

EXTC Engineering

DDC classification:

DDC23 006.31 OSI

Summary: Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts ""Streaming 101"" and ""Streaming 102"", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	School of Engineering & Technology	Circulation	006.31 OSI (Browse shelf(Opens below))	Available		E14536
Books	School of Engineering & Technology General Stacks	Circulation	006.31 OSI (Browse shelf(Opens below))	Checked out to SHAH AZEEM (GB24EC20)	05/05/2026	E14537

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Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way.

Expanded from Tyler Akidau’s popular blog posts ""Streaming 101"" and ""Streaming 102"", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.

You’ll explore:

How streaming and batch data processing patterns compare
The core principles and concepts behind robust out-of-order data processing
How watermarks track progress and completeness in infinite datasets
How exactly-once data processing techniques ensure correctness
How the concepts of streams and tables form the foundations of both batch and streaming data processing
The practical motivations behind a powerful persistent state mechanism, driven by a real-world example
How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

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