The shape of data: network science, geometry-based machine learning, and topological data analysis in R
"The Shape of Data shows how to use geometry- and topology-based algorithms for machine learning. The book focuses on practical applications rather than dense mathematical concepts, with coding examples using social network data, text data, medical data, and education data"--
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
San Francisco, CA
No Starch Press
[2023]
|
| Schlagworte: | |
| Zusammenfassung: | "The Shape of Data shows how to use geometry- and topology-based algorithms for machine learning. The book focuses on practical applications rather than dense mathematical concepts, with coding examples using social network data, text data, medical data, and education data"-- |
| Beschreibung: | Includes bibliographical references. - Description based on print version record and CIP data provided by publisher; resource not viewed |
| Beschreibung: | xxiii, 233 Seiten Illustrationen, Diagramme |
| ISBN: | 9781718503083 |
Internformat
MARC
| LEADER | 00000nam a22000001c 4500 | ||
|---|---|---|---|
| 001 | BV049332806 | ||
| 003 | DE-604 | ||
| 005 | 20231130 | ||
| 007 | t | ||
| 008 | 230919s2023 a||| |||| 00||| eng d | ||
| 020 | |a 9781718503083 |9 978-1-71850-308-3 | ||
| 035 | |a (OCoLC)1398174480 | ||
| 035 | |a (DE-599)BVBBV049332806 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-92 | ||
| 082 | 0 | |a 006.3/1 |2 23 | |
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 084 | |a ST 601 |0 (DE-625)143682: |2 rvk | ||
| 100 | 1 | |a Farrelly, Colleen |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a The shape of data |b network science, geometry-based machine learning, and topological data analysis in R |c by Colleen M. Farrelly and Yaé Ulrich Gaba |
| 264 | 1 | |a San Francisco, CA |b No Starch Press |c [2023] | |
| 300 | |a xxiii, 233 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references. - Description based on print version record and CIP data provided by publisher; resource not viewed | ||
| 520 | 3 | |a "The Shape of Data shows how to use geometry- and topology-based algorithms for machine learning. The book focuses on practical applications rather than dense mathematical concepts, with coding examples using social network data, text data, medical data, and education data"-- | |
| 650 | 0 | 7 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenanalyse |0 (DE-588)4123037-1 |2 gnd |9 rswk-swf |
| 653 | 0 | |a Geometric programming | |
| 653 | 0 | |a Topology | |
| 653 | 0 | |a Machine learning | |
| 653 | 0 | |a System analysis / Data processing | |
| 653 | 0 | |a R (Computer program language) | |
| 653 | 0 | |a Geometric programming | |
| 653 | 0 | |a Machine learning | |
| 653 | 0 | |a R (Computer program language) | |
| 653 | 0 | |a System analysis ; Data processing | |
| 653 | 0 | |a Topology | |
| 689 | 0 | 0 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |D s |
| 689 | 0 | 1 | |a Datenanalyse |0 (DE-588)4123037-1 |D s |
| 689 | 0 | 2 | |a R |g Programm |0 (DE-588)4705956-4 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Gaba, Yaé Ulrich |e Verfasser |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-7185-0309-0 |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-034593523 | ||
Datensatz im Suchindex
| _version_ | 1804185850007781376 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Farrelly, Colleen Gaba, Yaé Ulrich |
| author_facet | Farrelly, Colleen Gaba, Yaé Ulrich |
| author_role | aut aut |
| author_sort | Farrelly, Colleen |
| author_variant | c f cf y u g yu yug |
| building | Verbundindex |
| bvnumber | BV049332806 |
| classification_rvk | ST 300 ST 601 |
| ctrlnum | (OCoLC)1398174480 (DE-599)BVBBV049332806 |
| 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 |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02290nam a22005411c 4500</leader><controlfield tag="001">BV049332806</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20231130 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">230919s2023 a||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781718503083</subfield><subfield code="9">978-1-71850-308-3</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1398174480</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049332806</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-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/1</subfield><subfield code="2">23</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="084" ind1=" " ind2=" "><subfield code="a">ST 601</subfield><subfield code="0">(DE-625)143682:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Farrelly, Colleen</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The shape of data</subfield><subfield code="b">network science, geometry-based machine learning, and topological data analysis in R</subfield><subfield code="c">by Colleen M. Farrelly and Yaé Ulrich Gaba</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">San Francisco, CA</subfield><subfield code="b">No Starch Press</subfield><subfield code="c">[2023]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xxiii, 233 Seiten</subfield><subfield code="b">Illustrationen, Diagramme</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">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references. - Description based on print version record and CIP data provided by publisher; resource not viewed</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">"The Shape of Data shows how to use geometry- and topology-based algorithms for machine learning. The book focuses on practical applications rather than dense mathematical concepts, with coding examples using social network data, text data, medical data, and education data"--</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="650" ind1="0" ind2="7"><subfield code="a">R</subfield><subfield code="g">Programm</subfield><subfield code="0">(DE-588)4705956-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Datenanalyse</subfield><subfield code="0">(DE-588)4123037-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Geometric programming</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Topology</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">System analysis / Data processing</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R (Computer program language)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Geometric programming</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Machine learning</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R (Computer program language)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">System analysis ; Data processing</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Topology</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="1"><subfield code="a">Datenanalyse</subfield><subfield code="0">(DE-588)4123037-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">R</subfield><subfield code="g">Programm</subfield><subfield code="0">(DE-588)4705956-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gaba, Yaé Ulrich</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-1-7185-0309-0</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034593523</subfield></datafield></record></collection> |
| id | DE-604.BV049332806 |
| illustrated | Illustrated |
| index_date | 2024-07-03T22:45:39Z |
| indexdate | 2024-07-10T10:01:47Z |
| institution | BVB |
| isbn | 9781718503083 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034593523 |
| oclc_num | 1398174480 |
| open_access_boolean | |
| owner | DE-92 |
| owner_facet | DE-92 |
| physical | xxiii, 233 Seiten Illustrationen, Diagramme |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | No Starch Press |
| record_format | marc |
| spelling | Farrelly, Colleen Verfasser aut The shape of data network science, geometry-based machine learning, and topological data analysis in R by Colleen M. Farrelly and Yaé Ulrich Gaba San Francisco, CA No Starch Press [2023] xxiii, 233 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references. - Description based on print version record and CIP data provided by publisher; resource not viewed "The Shape of Data shows how to use geometry- and topology-based algorithms for machine learning. The book focuses on practical applications rather than dense mathematical concepts, with coding examples using social network data, text data, medical data, and education data"-- Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Geometric programming Topology Machine learning System analysis / Data processing R (Computer program language) System analysis ; Data processing Maschinelles Lernen (DE-588)4193754-5 s Datenanalyse (DE-588)4123037-1 s R Programm (DE-588)4705956-4 s DE-604 Gaba, Yaé Ulrich Verfasser aut Erscheint auch als Online-Ausgabe 978-1-7185-0309-0 |
| spellingShingle | Farrelly, Colleen Gaba, Yaé Ulrich The shape of data network science, geometry-based machine learning, and topological data analysis in R Maschinelles Lernen (DE-588)4193754-5 gnd R Programm (DE-588)4705956-4 gnd Datenanalyse (DE-588)4123037-1 gnd |
| subject_GND | (DE-588)4193754-5 (DE-588)4705956-4 (DE-588)4123037-1 |
| title | The shape of data network science, geometry-based machine learning, and topological data analysis in R |
| title_auth | The shape of data network science, geometry-based machine learning, and topological data analysis in R |
| title_exact_search | The shape of data network science, geometry-based machine learning, and topological data analysis in R |
| title_exact_search_txtP | The shape of data network science, geometry-based machine learning, and topological data analysis in R |
| title_full | The shape of data network science, geometry-based machine learning, and topological data analysis in R by Colleen M. Farrelly and Yaé Ulrich Gaba |
| title_fullStr | The shape of data network science, geometry-based machine learning, and topological data analysis in R by Colleen M. Farrelly and Yaé Ulrich Gaba |
| title_full_unstemmed | The shape of data network science, geometry-based machine learning, and topological data analysis in R by Colleen M. Farrelly and Yaé Ulrich Gaba |
| title_short | The shape of data |
| title_sort | the shape of data network science geometry based machine learning and topological data analysis in r |
| title_sub | network science, geometry-based machine learning, and topological data analysis in R |
| topic | Maschinelles Lernen (DE-588)4193754-5 gnd R Programm (DE-588)4705956-4 gnd Datenanalyse (DE-588)4123037-1 gnd |
| topic_facet | Maschinelles Lernen R Programm Datenanalyse |
| work_keys_str_mv | AT farrellycolleen theshapeofdatanetworksciencegeometrybasedmachinelearningandtopologicaldataanalysisinr AT gabayaeulrich theshapeofdatanetworksciencegeometrybasedmachinelearningandtopologicaldataanalysisinr |