Considering TensorFlow for the enterprise: an overview of the deep learning ecosystem
Deep learning is enabling the next generation of successful companies. The question is no longer whether enterprises will use deep learning (they will), but how involved each organization becomes with the technology. Sean Murphy and Allen Leis introduce deep learning from an enterprise perspective a...
Gespeichert in:
Beteiligte Personen: | , |
---|---|
Format: | Elektronisch E-Book |
Sprache: | Englisch |
Veröffentlicht: |
Sebastopol, CA
O'Reilly Media
[2017]
|
Ausgabe: | First edition. |
Schlagwörter: | |
Links: | https://learning.oreilly.com/library/view/-/9781491995075/?ar |
Zusammenfassung: | Deep learning is enabling the next generation of successful companies. The question is no longer whether enterprises will use deep learning (they will), but how involved each organization becomes with the technology. Sean Murphy and Allen Leis introduce deep learning from an enterprise perspective and offer an overview of the TensorFlow library and ecosystem. If your company is adopting deep learning, this report will help you navigate the initial decisions you must make--from choosing a deep learning framework to integrating deep learning with the other data analysis systems already in place--to ensure you're building a system capable of handling your specific business needs. Explore fundamental concepts and core questions about deep learning in the enterprise Familiarize yourself with available framework options, including TensorFlow, MXNet, Microsoft Cognitive Toolkit, and Deeplearning4J Dive into TensorFlow's library and ecosystem, from tools such as estimators, prebuilt neural networks, Keras, ML Toolkit for TensorFlow, Tensor2Tensor (T2T), TensorBoard, and TensorFlow Debugger, to model deployment and management with TensorFlow Serving See how companies such as Jet.com and PingThings have implemented deep learning to improve the accuracy and enhance the performance of a number of tasks. |
Beschreibung: | Includes bibliographical references. - Online resource; title from title page (Safari, viewed January 9, 2019) |
Umfang: | 1 Online-Ressource (1 volume) illustrations |
Internformat
MARC
LEADER | 00000cam a22000002 4500 | ||
---|---|---|---|
001 | ZDB-30-ORH-047622636 | ||
003 | DE-627-1 | ||
005 | 20240228120631.0 | ||
007 | cr uuu---uuuuu | ||
008 | 191023s2017 xx |||||o 00| ||eng c | ||
035 | |a (DE-627-1)047622636 | ||
035 | |a (DE-599)KEP047622636 | ||
035 | |a (ORHE)9781491995075 | ||
035 | |a (DE-627-1)047622636 | ||
040 | |a DE-627 |b ger |c DE-627 |e rda | ||
041 | |a eng | ||
100 | 1 | |a Murphy, Sean Patrick |e VerfasserIn |4 aut | |
245 | 1 | 0 | |a Considering TensorFlow for the enterprise |b an overview of the deep learning ecosystem |c Sean Murphy and Allen Leis |
250 | |a First edition. | ||
264 | 1 | |a Sebastopol, CA |b O'Reilly Media |c [2017] | |
264 | 4 | |c ©2018 | |
300 | |a 1 Online-Ressource (1 volume) |b illustrations | ||
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Includes bibliographical references. - Online resource; title from title page (Safari, viewed January 9, 2019) | ||
520 | |a Deep learning is enabling the next generation of successful companies. The question is no longer whether enterprises will use deep learning (they will), but how involved each organization becomes with the technology. Sean Murphy and Allen Leis introduce deep learning from an enterprise perspective and offer an overview of the TensorFlow library and ecosystem. If your company is adopting deep learning, this report will help you navigate the initial decisions you must make--from choosing a deep learning framework to integrating deep learning with the other data analysis systems already in place--to ensure you're building a system capable of handling your specific business needs. Explore fundamental concepts and core questions about deep learning in the enterprise Familiarize yourself with available framework options, including TensorFlow, MXNet, Microsoft Cognitive Toolkit, and Deeplearning4J Dive into TensorFlow's library and ecosystem, from tools such as estimators, prebuilt neural networks, Keras, ML Toolkit for TensorFlow, Tensor2Tensor (T2T), TensorBoard, and TensorFlow Debugger, to model deployment and management with TensorFlow Serving See how companies such as Jet.com and PingThings have implemented deep learning to improve the accuracy and enhance the performance of a number of tasks. | ||
630 | 2 | 0 | |a TensorFlow (Electronic resource) |
650 | 0 | |a Machine learning | |
650 | 0 | |a Artificial intelligence | |
650 | 0 | |a Electronic data processing |x Management | |
650 | 0 | |a Business enterprises |x Data processing | |
650 | 2 | |a Artificial Intelligence | |
650 | 2 | |a Machine Learning | |
650 | 4 | |a Apprentissage automatique | |
650 | 4 | |a Intelligence artificielle | |
650 | 4 | |a Entreprises ; Informatique | |
650 | 4 | |a artificial intelligence | |
650 | 4 | |a Artificial intelligence | |
650 | 4 | |a Business enterprises ; Data processing | |
650 | 4 | |a Electronic data processing ; Management | |
650 | 4 | |a Machine learning | |
700 | 1 | |a Leis, Allen |e VerfasserIn |4 aut | |
966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781491995075/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
912 | |a ZDB-30-ORH | ||
912 | |a ZDB-30-ORH | ||
951 | |a BO | ||
912 | |a ZDB-30-ORH | ||
049 | |a DE-91 |
Datensatz im Suchindex
DE-BY-TUM_katkey | ZDB-30-ORH-047622636 |
---|---|
_version_ | 1821494871932796928 |
adam_text | |
any_adam_object | |
author | Murphy, Sean Patrick Leis, Allen |
author_facet | Murphy, Sean Patrick Leis, Allen |
author_role | aut aut |
author_sort | Murphy, Sean Patrick |
author_variant | s p m sp spm a l al |
building | Verbundindex |
bvnumber | localTUM |
collection | ZDB-30-ORH |
ctrlnum | (DE-627-1)047622636 (DE-599)KEP047622636 (ORHE)9781491995075 |
edition | First edition. |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03215cam a22005292 4500</leader><controlfield tag="001">ZDB-30-ORH-047622636</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240228120631.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">191023s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047622636</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP047622636</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781491995075</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047622636</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Murphy, Sean Patrick</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Considering TensorFlow for the enterprise</subfield><subfield code="b">an overview of the deep learning ecosystem</subfield><subfield code="c">Sean Murphy and Allen Leis</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">First edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Sebastopol, CA</subfield><subfield code="b">O'Reilly Media</subfield><subfield code="c">[2017]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2018</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (1 volume)</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references. - Online resource; title from title page (Safari, viewed January 9, 2019)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Deep learning is enabling the next generation of successful companies. The question is no longer whether enterprises will use deep learning (they will), but how involved each organization becomes with the technology. Sean Murphy and Allen Leis introduce deep learning from an enterprise perspective and offer an overview of the TensorFlow library and ecosystem. If your company is adopting deep learning, this report will help you navigate the initial decisions you must make--from choosing a deep learning framework to integrating deep learning with the other data analysis systems already in place--to ensure you're building a system capable of handling your specific business needs. Explore fundamental concepts and core questions about deep learning in the enterprise Familiarize yourself with available framework options, including TensorFlow, MXNet, Microsoft Cognitive Toolkit, and Deeplearning4J Dive into TensorFlow's library and ecosystem, from tools such as estimators, prebuilt neural networks, Keras, ML Toolkit for TensorFlow, Tensor2Tensor (T2T), TensorBoard, and TensorFlow Debugger, to model deployment and management with TensorFlow Serving See how companies such as Jet.com and PingThings have implemented deep learning to improve the accuracy and enhance the performance of a number of tasks.</subfield></datafield><datafield tag="630" ind1="2" ind2="0"><subfield code="a">TensorFlow (Electronic resource)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Electronic data processing</subfield><subfield code="x">Management</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Business enterprises</subfield><subfield code="x">Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Artificial Intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Machine Learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Apprentissage automatique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Intelligence artificielle</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Entreprises ; Informatique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Business enterprises ; Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electronic data processing ; Management</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Leis, Allen</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781491995075/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
id | ZDB-30-ORH-047622636 |
illustrated | Illustrated |
indexdate | 2025-01-17T11:21:16Z |
institution | BVB |
language | English |
open_access_boolean | |
owner | DE-91 DE-BY-TUM |
owner_facet | DE-91 DE-BY-TUM |
physical | 1 Online-Ressource (1 volume) illustrations |
psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
publishDate | 2017 |
publishDateSearch | 2017 |
publishDateSort | 2017 |
publisher | O'Reilly Media |
record_format | marc |
spelling | Murphy, Sean Patrick VerfasserIn aut Considering TensorFlow for the enterprise an overview of the deep learning ecosystem Sean Murphy and Allen Leis First edition. Sebastopol, CA O'Reilly Media [2017] ©2018 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references. - Online resource; title from title page (Safari, viewed January 9, 2019) Deep learning is enabling the next generation of successful companies. The question is no longer whether enterprises will use deep learning (they will), but how involved each organization becomes with the technology. Sean Murphy and Allen Leis introduce deep learning from an enterprise perspective and offer an overview of the TensorFlow library and ecosystem. If your company is adopting deep learning, this report will help you navigate the initial decisions you must make--from choosing a deep learning framework to integrating deep learning with the other data analysis systems already in place--to ensure you're building a system capable of handling your specific business needs. Explore fundamental concepts and core questions about deep learning in the enterprise Familiarize yourself with available framework options, including TensorFlow, MXNet, Microsoft Cognitive Toolkit, and Deeplearning4J Dive into TensorFlow's library and ecosystem, from tools such as estimators, prebuilt neural networks, Keras, ML Toolkit for TensorFlow, Tensor2Tensor (T2T), TensorBoard, and TensorFlow Debugger, to model deployment and management with TensorFlow Serving See how companies such as Jet.com and PingThings have implemented deep learning to improve the accuracy and enhance the performance of a number of tasks. TensorFlow (Electronic resource) Machine learning Artificial intelligence Electronic data processing Management Business enterprises Data processing Artificial Intelligence Machine Learning Apprentissage automatique Intelligence artificielle Entreprises ; Informatique artificial intelligence Business enterprises ; Data processing Electronic data processing ; Management Leis, Allen VerfasserIn aut |
spellingShingle | Murphy, Sean Patrick Leis, Allen Considering TensorFlow for the enterprise an overview of the deep learning ecosystem TensorFlow (Electronic resource) Machine learning Artificial intelligence Electronic data processing Management Business enterprises Data processing Artificial Intelligence Machine Learning Apprentissage automatique Intelligence artificielle Entreprises ; Informatique artificial intelligence Business enterprises ; Data processing Electronic data processing ; Management |
title | Considering TensorFlow for the enterprise an overview of the deep learning ecosystem |
title_auth | Considering TensorFlow for the enterprise an overview of the deep learning ecosystem |
title_exact_search | Considering TensorFlow for the enterprise an overview of the deep learning ecosystem |
title_full | Considering TensorFlow for the enterprise an overview of the deep learning ecosystem Sean Murphy and Allen Leis |
title_fullStr | Considering TensorFlow for the enterprise an overview of the deep learning ecosystem Sean Murphy and Allen Leis |
title_full_unstemmed | Considering TensorFlow for the enterprise an overview of the deep learning ecosystem Sean Murphy and Allen Leis |
title_short | Considering TensorFlow for the enterprise |
title_sort | considering tensorflow for the enterprise an overview of the deep learning ecosystem |
title_sub | an overview of the deep learning ecosystem |
topic | TensorFlow (Electronic resource) Machine learning Artificial intelligence Electronic data processing Management Business enterprises Data processing Artificial Intelligence Machine Learning Apprentissage automatique Intelligence artificielle Entreprises ; Informatique artificial intelligence Business enterprises ; Data processing Electronic data processing ; Management |
topic_facet | TensorFlow (Electronic resource) Machine learning Artificial intelligence Electronic data processing Management Business enterprises Data processing Artificial Intelligence Machine Learning Apprentissage automatique Intelligence artificielle Entreprises ; Informatique artificial intelligence Business enterprises ; Data processing Electronic data processing ; Management |
work_keys_str_mv | AT murphyseanpatrick consideringtensorflowfortheenterpriseanoverviewofthedeeplearningecosystem AT leisallen consideringtensorflowfortheenterpriseanoverviewofthedeeplearningecosystem |