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03078cam a2200409Ii 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
jomaaum |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20230819111549.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION |
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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200718t20202020caua o ||| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781492053194 |
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|---|
| International Standard Book Number |
1492053198 |
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|---|
| International Standard Book Number |
1492053147 |
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|---|
| International Standard Book Number |
9781492053149 |
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|---|
| International Standard Book Number |
9781492053163 |
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|---|
| International Standard Book Number |
1492053163 |
| 024 8# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
9781492053187 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q325.5 |
| Item number |
.H36 2020 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.31 |
| Edition number |
23 |
| Item number |
H252 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Hapke, Hannes Max, |
| Relator term |
author |
| 9 (RLIN) |
45347 |
| 245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Title |
Building machine learning pipelines : |
| Remainder of title |
automating model life cycles with TensorFlow / |
| Statement of responsibility, etc |
Hannes Hapke and Catherine Nelson |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Sebastopol, CA : |
| Name of publisher, distributor, etc |
O'Reilly Media, |
| Date of publication, distribution, etc |
2020. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxv, 337 p. : |
| Other physical details |
ill. ; |
| Dimensions |
24 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index |
| 506 ## - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Available to OhioLINK libraries |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. The book also explores new approaches for integrating data privacy into machine learning pipelines. Understand the machine learning management lifecycle Implement data pipelines with Apache Airflow and Kubeflow Pipelines Work with data using TensorFlow tools like ML Metadata, TensorFlow Data Validation, and TensorFlow Transform Analyze models with TensorFlow Model Analysis and ship them with the TFX Model Pusher Component after the ModelValidator TFX Component confirmed that the analysis results are an improvement Deploy models in a variety of environments with TensorFlow Serving, TensorFlow Lite, and TensorFlow.js Learn methods for adding privacy, including differential privacy with TensorFlow Privacy and federated learning with TensorFlow Federated Design model feedback loops to increase your data sets and learn when to update your machine learning models |
| 630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
TensorFlow |
| 9 (RLIN) |
44847 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
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|---|
| Topical term or geographic name as entry element |
Cloud computing |
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|---|
| Topical term or geographic name as entry element |
Business enterprises |
| General subdivision |
Data processing |
| 9 (RLIN) |
42724 |
| 655 #4 - INDEX TERM--GENRE/FORM |
|---|
| Genre/form data or focus term |
Electronic books |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nelson, Catherine, |
| Relator term |
author |
| 9 (RLIN) |
45348 |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Ohio Library and Information Network |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Print version: |
| Main entry heading |
Hapke, Hannes |
| Title |
Building Machine Learning Pipelines |
| Place, publisher, and date of publication |
Sebastopol : O'Reilly Media, Incorporated,c2020 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Safari Books Online |
| Public note |
Connect to resource |
| Uniform Resource Identifier |
https://learning.oreilly.com/library/view/~/9781492053187/?ar |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Book |
