Deep learning cookbook : Practical recipes to get started quickly
By: Osinga, Douwe
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Publisher: Navi Mumbai 2018Edition: 1st.Description: xv, 234p. | Binding - Paperback | 22.8*17.8 cm.ISBN: 9789352137572.Subject(s): EXTC EngineeringDDC classification: 006.31 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
| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
Text Books
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School of Engineering & Technology | Circulation | 006.31 OSI (Browse shelf) | Available | E14536 | ||
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Text Books
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School of Engineering & Technology General Stacks | Circulation | 006.31 OSI (Browse shelf) | Available | E14537 |
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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