Machine learning fundamentals a concise introduction
This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes wide...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cambridge
Cambridge University Press
[2021]
|
Schlagworte: | |
Online-Zugang: | BSB01 FHN01 TUM01 UER01 UPA01 URL des Erstveröffentlichers |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
MARC
LEADER | 00000nmm a2200000zc 4500 | ||
---|---|---|---|
001 | BV047655340 | ||
003 | DE-604 | ||
005 | 20221205 | ||
007 | cr|uuu---uuuuu | ||
008 | 211228s2021 |||| o||u| ||||||eng d | ||
020 | |a 9781108938051 |c Online |9 978-1-108-93805-1 | ||
024 | 7 | |a 10.1017/9781108938051 |2 doi | |
035 | |a (ZDB-20-CBO)CR9781108938051 | ||
035 | |a (OCoLC)1291615202 | ||
035 | |a (DE-599)BVBBV047655340 | ||
040 | |a DE-604 |b ger |e rda | ||
041 | 0 | |a eng | |
049 | |a DE-12 |a DE-739 |a DE-29 |a DE-92 |a DE-91 | ||
082 | 0 | |a 006.3/1 | |
084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
100 | 1 | |a Jiang, Hui |e Verfasser |0 (DE-588)1247636526 |4 aut | |
245 | 1 | 0 | |a Machine learning fundamentals |b a concise introduction |c Hui Jiang |
264 | 1 | |a Cambridge |b Cambridge University Press |c [2021] | |
264 | 4 | |c © 2021 | |
300 | |a 1 Online-Ressource (xviii, 380 Seiten) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
520 | |a This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely "from scratch" based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts | ||
650 | 4 | |a Machine learning | |
650 | 0 | 7 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |2 gnd |9 rswk-swf |
689 | 0 | 0 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |D s |
689 | 0 | |5 DE-604 | |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, Hardcover |z 978-1-108-83704-0 |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, Paperback |z 978-1-108-94002-3 |
856 | 4 | 0 | |u https://doi.org/10.1017/9781108938051 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
912 | |a ZDB-20-CBO | ||
999 | |a oai:aleph.bib-bvb.de:BVB01-033040281 | ||
966 | e | |u https://doi.org/10.1017/9781108938051 |l BSB01 |p ZDB-20-CBO |q BSB_PDA_CBO |x Verlag |3 Volltext | |
966 | e | |u https://doi.org/10.1017/9781108938051 |l FHN01 |p ZDB-20-CBO |q FHN_PDA_CBO |x Verlag |3 Volltext | |
966 | e | |u https://doi.org/10.1017/9781108938051 |l TUM01 |p ZDB-20-CBO |q TUM_Paketkauf_2021 |x Verlag |3 Volltext | |
966 | e | |u https://doi.org/10.1017/9781108938051 |l UER01 |p ZDB-20-CBO |q UER_PDA_CBO_Kauf_2022 |x Verlag |3 Volltext | |
966 | e | |u https://doi.org/10.1017/9781108938051 |l UPA01 |p ZDB-20-CBO |q UPA_PDA_CBO_Kauf2021 |x Verlag |3 Volltext |
Datensatz im Suchindex
DE-BY-TUM_katkey | 2702923 |
---|---|
DE-BY-TUM_local_url | Verlag https://doi.org/10.1017/9781108938051 |
_version_ | 1816714876253372416 |
adam_txt | |
any_adam_object | |
any_adam_object_boolean | |
author | Jiang, Hui |
author_GND | (DE-588)1247636526 |
author_facet | Jiang, Hui |
author_role | aut |
author_sort | Jiang, Hui |
author_variant | h j hj |
building | Verbundindex |
bvnumber | BV047655340 |
classification_rvk | ST 300 |
collection | ZDB-20-CBO |
ctrlnum | (ZDB-20-CBO)CR9781108938051 (OCoLC)1291615202 (DE-599)BVBBV047655340 |
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 |
discipline_str_mv | Informatik |
doi_str_mv | 10.1017/9781108938051 |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02909nmm a2200481zc 4500</leader><controlfield tag="001">BV047655340</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20221205 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">211228s2021 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781108938051</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-108-93805-1</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1017/9781108938051</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-20-CBO)CR9781108938051</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1291615202</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047655340</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-91</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/1</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jiang, Hui</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1247636526</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Machine learning fundamentals</subfield><subfield code="b">a concise introduction</subfield><subfield code="c">Hui Jiang</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xviii, 380 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely "from scratch" based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe, Hardcover</subfield><subfield code="z">978-1-108-83704-0</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe, Paperback</subfield><subfield code="z">978-1-108-94002-3</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1017/9781108938051</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CBO</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033040281</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108938051</subfield><subfield code="l">BSB01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">BSB_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108938051</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">FHN_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108938051</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">TUM_Paketkauf_2021</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108938051</subfield><subfield code="l">UER01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">UER_PDA_CBO_Kauf_2022</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/9781108938051</subfield><subfield code="l">UPA01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">UPA_PDA_CBO_Kauf2021</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
id | DE-604.BV047655340 |
illustrated | Not Illustrated |
index_date | 2024-07-03T18:50:58Z |
indexdate | 2024-11-25T18:02:39Z |
institution | BVB |
isbn | 9781108938051 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033040281 |
oclc_num | 1291615202 |
open_access_boolean | |
owner | DE-12 DE-739 DE-29 DE-92 DE-91 DE-BY-TUM |
owner_facet | DE-12 DE-739 DE-29 DE-92 DE-91 DE-BY-TUM |
physical | 1 Online-Ressource (xviii, 380 Seiten) |
psigel | ZDB-20-CBO ZDB-20-CBO BSB_PDA_CBO ZDB-20-CBO FHN_PDA_CBO ZDB-20-CBO TUM_Paketkauf_2021 ZDB-20-CBO UER_PDA_CBO_Kauf_2022 ZDB-20-CBO UPA_PDA_CBO_Kauf2021 |
publishDate | 2021 |
publishDateSearch | 2021 |
publishDateSort | 2021 |
publisher | Cambridge University Press |
record_format | marc |
spellingShingle | Jiang, Hui Machine learning fundamentals a concise introduction Machine learning Maschinelles Lernen (DE-588)4193754-5 gnd |
subject_GND | (DE-588)4193754-5 |
title | Machine learning fundamentals a concise introduction |
title_auth | Machine learning fundamentals a concise introduction |
title_exact_search | Machine learning fundamentals a concise introduction |
title_exact_search_txtP | Machine learning fundamentals a concise introduction |
title_full | Machine learning fundamentals a concise introduction Hui Jiang |
title_fullStr | Machine learning fundamentals a concise introduction Hui Jiang |
title_full_unstemmed | Machine learning fundamentals a concise introduction Hui Jiang |
title_short | Machine learning fundamentals |
title_sort | machine learning fundamentals a concise introduction |
title_sub | a concise introduction |
topic | Machine learning Maschinelles Lernen (DE-588)4193754-5 gnd |
topic_facet | Machine learning Maschinelles Lernen |
url | https://doi.org/10.1017/9781108938051 |
work_keys_str_mv | AT jianghui machinelearningfundamentalsaconciseintroduction |