Designing deep learning systems:
A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems...
Gespeichert in:
Beteiligte Personen: | , |
---|---|
Format: | Elektronisch Video |
Sprache: | Englisch |
Veröffentlicht: |
[Place of publication not identified]
Manning Publications
2023
|
Ausgabe: | Video edition. |
Schlagwörter: | |
Links: | https://learning.oreilly.com/library/view/-/9781633439863VE/?ar |
Zusammenfassung: | A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. |
Beschreibung: | Online resource; title from title details screen (O'Reilly, viewed February 20, 2024) |
Umfang: | 1 Online-Ressource (1 video file (11 hr., 58 min.)) sound, color. |
Internformat
MARC
LEADER | 00000ngm a22000002 4500 | ||
---|---|---|---|
001 | ZDB-30-ORH-100861318 | ||
003 | DE-627-1 | ||
005 | 20240227122215.0 | ||
006 | m o | | | ||
007 | cr uuu---uuuuu | ||
008 | 240227s2023 xx ||| |o o ||eng c | ||
035 | |a (DE-627-1)100861318 | ||
035 | |a (DE-599)KEP100861318 | ||
035 | |a (ORHE)9781633439863VE | ||
035 | |a (DE-627-1)100861318 | ||
040 | |a DE-627 |b ger |c DE-627 |e rda | ||
041 | |a eng | ||
082 | 0 | |a 006.3/1 |2 23/eng/20240220 | |
100 | 1 | |a Wang, Chi |e VerfasserIn |4 aut | |
245 | 1 | 0 | |a Designing deep learning systems |c Chi Wang, Donald Szeto |
250 | |a Video edition. | ||
264 | 1 | |a [Place of publication not identified] |b Manning Publications |c 2023 | |
300 | |a 1 Online-Ressource (1 video file (11 hr., 58 min.)) |b sound, color. | ||
336 | |a zweidimensionales bewegtes Bild |b tdi |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Online resource; title from title details screen (O'Reilly, viewed February 20, 2024) | ||
520 | |a A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. | ||
650 | 0 | |a Deep learning (Machine learning) | |
650 | 0 | |a Machine learning | |
650 | 4 | |a Apprentissage profond | |
650 | 4 | |a Apprentissage automatique | |
650 | 4 | |a Instructional films | |
650 | 4 | |a Nonfiction films | |
650 | 4 | |a Internet videos | |
650 | 4 | |a Films de formation | |
650 | 4 | |a Films autres que de fiction | |
650 | 4 | |a Vidéos sur Internet | |
700 | 1 | |a Szeto, Donald |e VerfasserIn |4 aut | |
710 | 2 | |a Manning (Firm), |e Verlag |4 pbl | |
966 | 4 | 0 | |l DE-91 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781633439863VE/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
912 | |a ZDB-30-ORH | ||
935 | |c vide | ||
951 | |a BO | ||
912 | |a ZDB-30-ORH | ||
049 | |a DE-91 |
Datensatz im Suchindex
DE-BY-TUM_katkey | ZDB-30-ORH-100861318 |
---|---|
_version_ | 1821494934347186176 |
adam_text | |
any_adam_object | |
author | Wang, Chi Szeto, Donald |
author_facet | Wang, Chi Szeto, Donald |
author_role | aut aut |
author_sort | Wang, Chi |
author_variant | c w cw d s ds |
building | Verbundindex |
bvnumber | localTUM |
collection | ZDB-30-ORH |
ctrlnum | (DE-627-1)100861318 (DE-599)KEP100861318 (ORHE)9781633439863VE |
dewey-full | 006.3/1 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.3/1 |
dewey-search | 006.3/1 |
dewey-sort | 16.3 11 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
edition | Video edition. |
format | Electronic Video |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03500ngm a22004932 4500</leader><controlfield tag="001">ZDB-30-ORH-100861318</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240227122215.0</controlfield><controlfield tag="006">m o | | </controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240227s2023 xx ||| |o o ||eng c</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)100861318</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP100861318</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781633439863VE</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)100861318</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="082" ind1="0" ind2=" "><subfield code="a">006.3/1</subfield><subfield code="2">23/eng/20240220</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wang, Chi</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Designing deep learning systems</subfield><subfield code="c">Chi Wang, Donald Szeto</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">Video edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Place of publication not identified]</subfield><subfield code="b">Manning Publications</subfield><subfield code="c">2023</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (1 video file (11 hr., 58 min.))</subfield><subfield code="b">sound, color.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">zweidimensionales bewegtes Bild</subfield><subfield code="b">tdi</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">Online resource; title from title details screen (O'Reilly, viewed February 20, 2024)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Deep learning (Machine learning)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Apprentissage profond</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Apprentissage automatique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Instructional films</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Nonfiction films</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Internet videos</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Films de formation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Films autres que de fiction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Vidéos sur Internet</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Szeto, Donald</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">Manning (Firm),</subfield><subfield code="e">Verlag</subfield><subfield code="4">pbl</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/-/9781633439863VE/?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="935" ind1=" " ind2=" "><subfield code="c">vide</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-100861318 |
illustrated | Not Illustrated |
indexdate | 2025-01-17T11:22:16Z |
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 video file (11 hr., 58 min.)) sound, color. |
psigel | ZDB-30-ORH TUM_PDA_ORH ZDB-30-ORH |
publishDate | 2023 |
publishDateSearch | 2023 |
publishDateSort | 2023 |
publisher | Manning Publications |
record_format | marc |
spelling | Wang, Chi VerfasserIn aut Designing deep learning systems Chi Wang, Donald Szeto Video edition. [Place of publication not identified] Manning Publications 2023 1 Online-Ressource (1 video file (11 hr., 58 min.)) sound, color. zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title details screen (O'Reilly, viewed February 20, 2024) A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO. Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet Szeto, Donald VerfasserIn aut Manning (Firm), Verlag pbl |
spellingShingle | Wang, Chi Szeto, Donald Designing deep learning systems Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
title | Designing deep learning systems |
title_auth | Designing deep learning systems |
title_exact_search | Designing deep learning systems |
title_full | Designing deep learning systems Chi Wang, Donald Szeto |
title_fullStr | Designing deep learning systems Chi Wang, Donald Szeto |
title_full_unstemmed | Designing deep learning systems Chi Wang, Donald Szeto |
title_short | Designing deep learning systems |
title_sort | designing deep learning systems |
topic | Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
topic_facet | Deep learning (Machine learning) Machine learning Apprentissage profond Apprentissage automatique Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
work_keys_str_mv | AT wangchi designingdeeplearningsystems AT szetodonald designingdeeplearningsystems AT manningfirm designingdeeplearningsystems |