Machine Learning for Streaming Data with Python : (Record no. 8429)
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| 001 - CONTROL NUMBER | |
| control field | on1334106851 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OCoLC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20241121073040.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION | |
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| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220709s2022 enk o 000 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | EBLCP |
| Language of cataloging | eng |
| Description conventions | pn |
| Transcribing agency | EBLCP |
| Modifying agency | ORMDA |
| -- | UKMGB |
| -- | OCLCF |
| -- | OCLCQ |
| -- | N$T |
| -- | UKAHL |
| -- | OCLCQ |
| 015 ## - NATIONAL BIBLIOGRAPHY NUMBER | |
| National bibliography number | GBC2B2954 |
| Source | bnb |
| 016 7# - NATIONAL BIBLIOGRAPHIC AGENCY CONTROL NUMBER | |
| Record control number | 020661698 |
| Source | Uk |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1803242639 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781803242637 |
| Qualifying information | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Cancelled/invalid ISBN | 9781803248363 |
| Qualifying information | (pbk.) |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | 3320918 |
| -- | (N$T) |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC)1334106851 |
| 037 ## - SOURCE OF ACQUISITION | |
| Stock number | 9781803248363 |
| Source of stock number/acquisition | O'Reilly Media |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q325.5 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3/1 |
| Edition number | 23/eng/20220719 |
| 049 ## - LOCAL HOLDINGS (OCLC) | |
| Holding library | MAIN |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Korstanje, Joos. |
| 9 (RLIN) | 20668 |
| 245 10 - TITLE STATEMENT | |
| Title | Machine Learning for Streaming Data with Python : |
| Remainder of title | Rapidly Build Practical Online Machine Learning Solutions Using River and Other Top Key Frameworks / |
| Statement of responsibility, etc | Joos Korstanje. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Birmingham : |
| Name of publisher, distributor, etc | Packt Publishing, Limited, |
| Date of publication, distribution, etc | 2022. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource (258 pages) |
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| 338 ## - | |
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| -- | Print version record. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Apply machine learning to streaming data with the help of practical examples, and deal with challenges that surround streaming Key Features Work on streaming use cases that are not taught in most data science courses Gain experience with state-of-the-art tools for streaming data Mitigate various challenges while handling streaming data Book Description Streaming data is the new top technology to watch out for in the field of data science and machine learning. As business needs become more demanding, many use cases require real-time analysis as well as real-time machine learning. This book will help you to get up to speed with data analytics for streaming data and focus strongly on adapting machine learning and other analytics to the case of streaming data. You will first learn about the architecture for streaming and real-time machine learning. Next, you will look at the state-of-the-art frameworks for streaming data like River. Later chapters will focus on various industrial use cases for streaming data like Online Anomaly Detection and others. As you progress, you will discover various challenges and learn how to mitigate them. In addition to this, you will learn best practices that will help you use streaming data to generate real-time insights. By the end of this book, you will have gained the confidence you need to stream data in your machine learning models. What you will learn Understand the challenges and advantages of working with streaming data Develop real-time insights from streaming data Understand the implementation of streaming data with various use cases to boost your knowledge Develop a PCA alternative that can work on real-time data Explore best practices for handling streaming data that you absolutely need to remember Develop an API for real-time machine learning inference Who this book is for This book is for data scientists and machine learning engineers who have a background in machine learning, are practice and technology-oriented, and want to learn how to apply machine learning to streaming data through practical examples with modern technologies. Although an understanding of basic Python and machine learning concepts is a must, no prior knowledge of streaming is required. |
| 590 ## - LOCAL NOTE (RLIN) | |
| Local note | Added to collection customer.56279.3 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning. |
| 9 (RLIN) | 2890 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Python (Computer program language) |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning. |
| Source of heading or term | fast |
| -- | (OCoLC)fst01004795 |
| 9 (RLIN) | 2890 |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Python (Computer program language) |
| Source of heading or term | fast |
| -- | (OCoLC)fst01084736 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Print version: |
| Main entry heading | Korstanje, Joos. |
| Title | Machine Learning for Streaming Data with Python. |
| Place, publisher, and date of publication | Birmingham : Packt Publishing, Limited, �2022 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | EBSCOhost |
| Uniform Resource Identifier | <a href="https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3320918">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3320918</a> |
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