Deep learning and the game of Go:
The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can l...
Gespeichert in:
Beteiligte Personen: | , |
---|---|
Format: | Elektronisch E-Book |
Sprache: | Englisch |
Veröffentlicht: |
Shelter Island, NY
Manning Publications Co.
[2019]
|
Schlagwörter: | |
Links: | https://learning.oreilly.com/library/view/-/9781617295324/?ar |
Zusammenfassung: | The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! "Deep learning and the game of Go" introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios!-- |
Beschreibung: | Includes bibliographical references and index. - Online resource; title from title page (Safari, viewed April 2, 2019) |
Umfang: | 1 Online-Ressource (1 volume) illustrations |
Internformat
MARC
LEADER | 00000cam a22000002 4500 | ||
---|---|---|---|
001 | ZDB-30-ORH-047659165 | ||
003 | DE-627-1 | ||
005 | 20240228120704.0 | ||
007 | cr uuu---uuuuu | ||
008 | 191023s2019 xx |||||o 00| ||eng c | ||
035 | |a (DE-627-1)047659165 | ||
035 | |a (DE-599)KEP047659165 | ||
035 | |a (ORHE)9781617295324 | ||
035 | |a (DE-627-1)047659165 | ||
040 | |a DE-627 |b ger |c DE-627 |e rda | ||
041 | |a eng | ||
082 | 0 | |a 006.31 |2 23 | |
100 | 1 | |a Pumperla, Max |e VerfasserIn |4 aut | |
245 | 1 | 0 | |a Deep learning and the game of Go |c Max Pumperla and Kevin Ferguson |
264 | 1 | |a Shelter Island, NY |b Manning Publications Co. |c [2019] | |
264 | 4 | |c ©2019 | |
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 and index. - Online resource; title from title page (Safari, viewed April 2, 2019) | ||
520 | |a The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! "Deep learning and the game of Go" introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios!-- | ||
650 | 0 | |a Machine learning | |
650 | 0 | |a Go (Game) | |
650 | 0 | |a Artificial intelligence | |
650 | 0 | |a Reinforcement learning | |
650 | 0 | |a Neural networks (Computer science) | |
650 | 2 | |a Artificial Intelligence | |
650 | 2 | |a Neural Networks, Computer | |
650 | 2 | |a Machine Learning | |
650 | 4 | |a Apprentissage automatique | |
650 | 4 | |a Go (Jeu) | |
650 | 4 | |a Intelligence artificielle | |
650 | 4 | |a Apprentissage par renforcement (Intelligence artificielle) | |
650 | 4 | |a Réseaux neuronaux (Informatique) | |
650 | 4 | |a gō | |
650 | 4 | |a artificial intelligence | |
650 | 4 | |a go (board game) | |
650 | 4 | |a Artificial intelligence | |
650 | 4 | |a Go (Game) | |
650 | 4 | |a Machine learning | |
650 | 4 | |a Neural networks (Computer science) | |
650 | 4 | |a Reinforcement learning | |
700 | 1 | |a Ferguson, Kevin |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/-/9781617295324/?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-047659165 |
---|---|
_version_ | 1821494865634000896 |
adam_text | |
any_adam_object | |
author | Pumperla, Max Ferguson, Kevin |
author_facet | Pumperla, Max Ferguson, Kevin |
author_role | aut aut |
author_sort | Pumperla, Max |
author_variant | m p mp k f kf |
building | Verbundindex |
bvnumber | localTUM |
collection | ZDB-30-ORH |
ctrlnum | (DE-627-1)047659165 (DE-599)KEP047659165 (ORHE)9781617295324 |
dewey-full | 006.31 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.31 |
dewey-search | 006.31 |
dewey-sort | 16.31 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02810cam a22006012 4500</leader><controlfield tag="001">ZDB-30-ORH-047659165</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20240228120704.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">191023s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047659165</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP047659165</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781617295324</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)047659165</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">006.31</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Pumperla, Max</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Deep learning and the game of Go</subfield><subfield code="c">Max Pumperla and Kevin Ferguson</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Shelter Island, NY</subfield><subfield code="b">Manning Publications Co.</subfield><subfield code="c">[2019]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2019</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 and index. - Online resource; title from title page (Safari, viewed April 2, 2019)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! "Deep learning and the game of Go" introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios!--</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Go (Game)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Reinforcement learning</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Artificial Intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="2"><subfield code="a">Neural Networks, Computer</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">Go (Jeu)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Intelligence artificielle</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Apprentissage par renforcement (Intelligence artificielle)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Réseaux neuronaux (Informatique)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">gō</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">go (board game)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Go (Game)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Reinforcement learning</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ferguson, Kevin</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/-/9781617295324/?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-047659165 |
illustrated | Illustrated |
indexdate | 2025-01-17T11:21:10Z |
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 | 2019 |
publishDateSearch | 2019 |
publishDateSort | 2019 |
publisher | Manning Publications Co. |
record_format | marc |
spelling | Pumperla, Max VerfasserIn aut Deep learning and the game of Go Max Pumperla and Kevin Ferguson Shelter Island, NY Manning Publications Co. [2019] ©2019 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Online resource; title from title page (Safari, viewed April 2, 2019) The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! "Deep learning and the game of Go" introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios!-- Machine learning Go (Game) Artificial intelligence Reinforcement learning Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Go (Jeu) Intelligence artificielle Apprentissage par renforcement (Intelligence artificielle) Réseaux neuronaux (Informatique) gō artificial intelligence go (board game) Ferguson, Kevin VerfasserIn aut |
spellingShingle | Pumperla, Max Ferguson, Kevin Deep learning and the game of Go Machine learning Go (Game) Artificial intelligence Reinforcement learning Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Go (Jeu) Intelligence artificielle Apprentissage par renforcement (Intelligence artificielle) Réseaux neuronaux (Informatique) gō artificial intelligence go (board game) |
title | Deep learning and the game of Go |
title_auth | Deep learning and the game of Go |
title_exact_search | Deep learning and the game of Go |
title_full | Deep learning and the game of Go Max Pumperla and Kevin Ferguson |
title_fullStr | Deep learning and the game of Go Max Pumperla and Kevin Ferguson |
title_full_unstemmed | Deep learning and the game of Go Max Pumperla and Kevin Ferguson |
title_short | Deep learning and the game of Go |
title_sort | deep learning and the game of go |
topic | Machine learning Go (Game) Artificial intelligence Reinforcement learning Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Go (Jeu) Intelligence artificielle Apprentissage par renforcement (Intelligence artificielle) Réseaux neuronaux (Informatique) gō artificial intelligence go (board game) |
topic_facet | Machine learning Go (Game) Artificial intelligence Reinforcement learning Neural networks (Computer science) Artificial Intelligence Neural Networks, Computer Machine Learning Apprentissage automatique Go (Jeu) Intelligence artificielle Apprentissage par renforcement (Intelligence artificielle) Réseaux neuronaux (Informatique) gō artificial intelligence go (board game) |
work_keys_str_mv | AT pumperlamax deeplearningandthegameofgo AT fergusonkevin deeplearningandthegameofgo |