Sound business practices for data mining and predictive analysis:
This course addresses the application of data mining and diagnostic analytics to measure business performance. It builds upon these business performance measurements to achieve advanced insights with predictive and perspective analytics. It examines common techniques that can be used to measure the...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic Video |
| Language: | English |
| Published: |
Piscataway, N.J.
IEEE Communications Society
2021
|
| Subjects: | |
| Online Access: | TUM01 Volltext |
| Summary: | This course addresses the application of data mining and diagnostic analytics to measure business performance. It builds upon these business performance measurements to achieve advanced insights with predictive and perspective analytics. It examines common techniques that can be used to measure the efficacy of machine learning integrations for business processes and reviews a real-world business case study in leveraging machine learning, advanced analytics, and process automation for reducing business operations costs |
| Item Description: | "Machine learning : predictive analysis for business decisions |
| Physical Description: | 1 Online-Ressource (1 Video-Datei, 34 Minuten) |
| ISBN: | 9781538686072 1538686074 |
Staff View
MARC
| LEADER | 00000ngm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047620244 | ||
| 003 | DE-604 | ||
| 005 | 20220113 | ||
| 006 | m|||| o||u| |||||| | ||
| 007 | vz|uuuuuu | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 211201s2021 ||| 0s vueng d | ||
| 020 | |a 9781538686072 |9 978-1-5386-8607-2 | ||
| 020 | |a 1538686074 |9 1-5386-8607-4 | ||
| 035 | |a (ZDB-37-ICG)on1240910338 | ||
| 035 | |a (OCoLC)1289764425 | ||
| 035 | |a (DE-599)BVBBV047620244 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91 | ||
| 082 | 0 | |a 006.312 | |
| 100 | 1 | |a Scott, Grant |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Sound business practices for data mining and predictive analysis |c Grant Scott |
| 264 | 1 | |a Piscataway, N.J. |b IEEE Communications Society |c 2021 | |
| 300 | |a 1 Online-Ressource (1 Video-Datei, 34 Minuten) | ||
| 336 | |b tdi |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a "Machine learning : predictive analysis for business decisions | ||
| 520 | |a This course addresses the application of data mining and diagnostic analytics to measure business performance. It builds upon these business performance measurements to achieve advanced insights with predictive and perspective analytics. It examines common techniques that can be used to measure the efficacy of machine learning integrations for business processes and reviews a real-world business case study in leveraging machine learning, advanced analytics, and process automation for reducing business operations costs | ||
| 650 | 4 | |a Data mining / fast / (OCoLC)fst00887946 | |
| 650 | 4 | |a Machine learning / fast / (OCoLC)fst01004795 | |
| 650 | 4 | |a Predictive analytics / fast / (OCoLC)fst02021979 | |
| 650 | 4 | |a Data mining | |
| 650 | 4 | |a Predictive analytics | |
| 650 | 4 | |a Machine learning | |
| 655 | 7 | |0 (DE-588)4017102-4 |a Film |2 gnd-content | |
| 856 | 4 | 0 | |u https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1592 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-37-ICG | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033004902 | ||
| 966 | e | |u https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1592 |l TUM01 |p ZDB-37-ICG |x Verlag |3 Volltext | |
Record in the Search Index
| _version_ | 1804183057905745920 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Scott, Grant |
| author_facet | Scott, Grant |
| author_role | aut |
| author_sort | Scott, Grant |
| author_variant | g s gs |
| building | Verbundindex |
| bvnumber | BV047620244 |
| collection | ZDB-37-ICG |
| ctrlnum | (ZDB-37-ICG)on1240910338 (OCoLC)1289764425 (DE-599)BVBBV047620244 |
| dewey-full | 006.312 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.312 |
| dewey-search | 006.312 |
| dewey-sort | 16.312 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Electronic Video |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02160ngm a2200457zc 4500</leader><controlfield tag="001">BV047620244</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20220113 </controlfield><controlfield tag="006">m|||| o||u| ||||||</controlfield><controlfield tag="007">vz|uuuuuu</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">211201s2021 ||| 0s vueng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781538686072</subfield><subfield code="9">978-1-5386-8607-2</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1538686074</subfield><subfield code="9">1-5386-8607-4</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-37-ICG)on1240910338</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1289764425</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047620244</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-91</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.312</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Scott, Grant</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Sound business practices for data mining and predictive analysis</subfield><subfield code="c">Grant Scott</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Piscataway, N.J.</subfield><subfield code="b">IEEE Communications Society</subfield><subfield code="c">2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (1 Video-Datei, 34 Minuten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">tdi</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="500" ind1=" " ind2=" "><subfield code="a">"Machine learning : predictive analysis for business decisions</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This course addresses the application of data mining and diagnostic analytics to measure business performance. It builds upon these business performance measurements to achieve advanced insights with predictive and perspective analytics. It examines common techniques that can be used to measure the efficacy of machine learning integrations for business processes and reviews a real-world business case study in leveraging machine learning, advanced analytics, and process automation for reducing business operations costs</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data mining / fast / (OCoLC)fst00887946</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning / fast / (OCoLC)fst01004795</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Predictive analytics / fast / (OCoLC)fst02021979</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Predictive analytics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4017102-4</subfield><subfield code="a">Film</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1592</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-37-ICG</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033004902</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1592</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-37-ICG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| genre | (DE-588)4017102-4 Film gnd-content |
| genre_facet | Film |
| id | DE-604.BV047620244 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:42:39Z |
| indexdate | 2024-07-10T09:17:24Z |
| institution | BVB |
| isbn | 9781538686072 1538686074 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033004902 |
| oclc_num | 1240910338 1289764425 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (1 Video-Datei, 34 Minuten) |
| psigel | ZDB-37-ICG |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | IEEE Communications Society |
| record_format | marc |
| spelling | Scott, Grant Verfasser aut Sound business practices for data mining and predictive analysis Grant Scott Piscataway, N.J. IEEE Communications Society 2021 1 Online-Ressource (1 Video-Datei, 34 Minuten) tdi rdacontent c rdamedia cr rdacarrier "Machine learning : predictive analysis for business decisions This course addresses the application of data mining and diagnostic analytics to measure business performance. It builds upon these business performance measurements to achieve advanced insights with predictive and perspective analytics. It examines common techniques that can be used to measure the efficacy of machine learning integrations for business processes and reviews a real-world business case study in leveraging machine learning, advanced analytics, and process automation for reducing business operations costs Data mining / fast / (OCoLC)fst00887946 Machine learning / fast / (OCoLC)fst01004795 Predictive analytics / fast / (OCoLC)fst02021979 Data mining Predictive analytics Machine learning (DE-588)4017102-4 Film gnd-content https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1592 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Scott, Grant Sound business practices for data mining and predictive analysis Data mining / fast / (OCoLC)fst00887946 Machine learning / fast / (OCoLC)fst01004795 Predictive analytics / fast / (OCoLC)fst02021979 Data mining Predictive analytics Machine learning |
| subject_GND | (DE-588)4017102-4 |
| title | Sound business practices for data mining and predictive analysis |
| title_auth | Sound business practices for data mining and predictive analysis |
| title_exact_search | Sound business practices for data mining and predictive analysis |
| title_exact_search_txtP | Sound business practices for data mining and predictive analysis |
| title_full | Sound business practices for data mining and predictive analysis Grant Scott |
| title_fullStr | Sound business practices for data mining and predictive analysis Grant Scott |
| title_full_unstemmed | Sound business practices for data mining and predictive analysis Grant Scott |
| title_short | Sound business practices for data mining and predictive analysis |
| title_sort | sound business practices for data mining and predictive analysis |
| topic | Data mining / fast / (OCoLC)fst00887946 Machine learning / fast / (OCoLC)fst01004795 Predictive analytics / fast / (OCoLC)fst02021979 Data mining Predictive analytics Machine learning |
| topic_facet | Data mining / fast / (OCoLC)fst00887946 Machine learning / fast / (OCoLC)fst01004795 Predictive analytics / fast / (OCoLC)fst02021979 Data mining Predictive analytics Machine learning Film |
| url | https://ieeexplore.ieee.org/servlet/opac?mdnumber=EW1592 |
| work_keys_str_mv | AT scottgrant soundbusinesspracticesfordataminingandpredictiveanalysis |