Predictive analytics for dummies:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, N.J.
Wiley
2014
|
| Schriftenreihe: | --For dummies
|
| Schlagworte: | |
| Online-Zugang: | TUM01 Volltext |
| Beschreibung: | Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big DataPredictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businessesHelps readers see how to shepherd predictive analytics projects through their companiesExplains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and moreCovers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing dataAlso covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewherePropose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies |
| Beschreibung: | 1 Online-Ressource (xii, 348 p.) |
| ISBN: | 111872920X 1118729412 9781118729205 9781118729410 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV041990654 | ||
| 003 | DE-604 | ||
| 005 | 20141010 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 140723s2014 |||| o||u| ||||||eng d | ||
| 020 | |a 111872920X |c electronic bk. |9 1-118-72920-X | ||
| 020 | |a 1118729412 |c electronic bk. |9 1-118-72941-2 | ||
| 020 | |a 9781118729205 |c electronic bk. |9 978-1-118-72920-5 | ||
| 020 | |a 9781118729410 |c electronic bk. |9 978-1-118-72941-0 | ||
| 035 | |a (OCoLC)864560209 | ||
| 035 | |a (DE-599)BVBBV041990654 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91 | ||
| 082 | 0 | |a 658.056312 |2 23 | |
| 084 | |a QH 234 |0 (DE-625)141549: |2 rvk | ||
| 084 | |a ST 530 |0 (DE-625)143679: |2 rvk | ||
| 100 | 1 | |a Bari, Anasse |e Verfasser |0 (DE-588)1050253795 |4 aut | |
| 245 | 1 | 0 | |a Predictive analytics for dummies |c Anasse Bari, Mohamed Chaouchi, and Tommy Jung |
| 264 | 1 | |a Hoboken, N.J. |b Wiley |c 2014 | |
| 300 | |a 1 Online-Ressource (xii, 348 p.) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a --For dummies | |
| 500 | |a Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big DataPredictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businessesHelps readers see how to shepherd predictive analytics projects through their companiesExplains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and moreCovers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing dataAlso covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewherePropose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies | ||
| 650 | 7 | |a BUSINESS & ECONOMICS / New Business Enterprises |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS / Industrial Management |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS / Management |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS / Management Science |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS / Organizational Behavior |2 bisacsh | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Wirtschaft | |
| 650 | 4 | |a Management / Data processing | |
| 650 | 4 | |a Management / Mathematical models | |
| 650 | 4 | |a Data mining | |
| 650 | 0 | 7 | |a Prognose |0 (DE-588)4047390-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Vorhersagetheorie |0 (DE-588)4188671-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Data Mining |0 (DE-588)4428654-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenmodell |0 (DE-588)4192516-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Big Data |0 (DE-588)4802620-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenmanagement |0 (DE-588)4213132-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenanalyse |0 (DE-588)4123037-1 |2 gnd |9 rswk-swf |
| 653 | |a Electronic books | ||
| 689 | 0 | 0 | |a Data Mining |0 (DE-588)4428654-5 |D s |
| 689 | 0 | 1 | |a Datenanalyse |0 (DE-588)4123037-1 |D s |
| 689 | 0 | 2 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |D s |
| 689 | 0 | 3 | |a Big Data |0 (DE-588)4802620-7 |D s |
| 689 | 0 | 4 | |a Vorhersagetheorie |0 (DE-588)4188671-9 |D s |
| 689 | 0 | 5 | |a Datenmodell |0 (DE-588)4192516-6 |D s |
| 689 | 0 | 6 | |a Datenmanagement |0 (DE-588)4213132-7 |D s |
| 689 | 0 | 7 | |a Prognose |0 (DE-588)4047390-9 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 700 | 1 | |a Chaouchi, Mohamed |e Sonstige |0 (DE-588)1050253884 |4 oth | |
| 700 | 1 | |a Jung, Tommy |e Sonstige |0 (DE-588)1050253949 |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe, Paperback |z 978-1-118-72896-3 |
| 856 | 4 | 0 | |u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=714691 |x Aggregator |3 Volltext |
| 912 | |a ZDB-4-NLEBK | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027432902 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=714691 |l TUM01 |p ZDB-4-NLEBK |q TUM_PDA_EBSCO_BAE_gekauft |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804152395024826368 |
|---|---|
| any_adam_object | |
| author | Bari, Anasse |
| author_GND | (DE-588)1050253795 (DE-588)1050253884 (DE-588)1050253949 |
| author_facet | Bari, Anasse |
| author_role | aut |
| author_sort | Bari, Anasse |
| author_variant | a b ab |
| building | Verbundindex |
| bvnumber | BV041990654 |
| classification_rvk | QH 234 ST 530 |
| collection | ZDB-4-NLEBK |
| ctrlnum | (OCoLC)864560209 (DE-599)BVBBV041990654 |
| dewey-full | 658.056312 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.056312 |
| dewey-search | 658.056312 |
| dewey-sort | 3658.056312 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Informatik Wirtschaftswissenschaften |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04942nmm a2200781zc 4500</leader><controlfield tag="001">BV041990654</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20141010 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">140723s2014 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">111872920X</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">1-118-72920-X</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1118729412</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">1-118-72941-2</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781118729205</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">978-1-118-72920-5</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781118729410</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">978-1-118-72941-0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)864560209</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV041990654</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</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">658.056312</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QH 234</subfield><subfield code="0">(DE-625)141549:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 530</subfield><subfield code="0">(DE-625)143679:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Bari, Anasse</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1050253795</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Predictive analytics for dummies</subfield><subfield code="c">Anasse Bari, Mohamed Chaouchi, and Tommy Jung</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hoboken, N.J.</subfield><subfield code="b">Wiley</subfield><subfield code="c">2014</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xii, 348 p.)</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="490" ind1="0" ind2=" "><subfield code="a">--For dummies</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big DataPredictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businessesHelps readers see how to shepherd predictive analytics projects through their companiesExplains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and moreCovers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing dataAlso covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewherePropose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">BUSINESS & ECONOMICS / New Business Enterprises</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">BUSINESS & ECONOMICS / Industrial Management</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">BUSINESS & ECONOMICS / Management</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">BUSINESS & ECONOMICS / Management Science</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">BUSINESS & ECONOMICS / Organizational Behavior</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Datenverarbeitung</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematisches Modell</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wirtschaft</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Management / Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Management / Mathematical models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Prognose</subfield><subfield code="0">(DE-588)4047390-9</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Vorhersagetheorie</subfield><subfield code="0">(DE-588)4188671-9</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Data Mining</subfield><subfield code="0">(DE-588)4428654-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Datenmodell</subfield><subfield code="0">(DE-588)4192516-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Datenmanagement</subfield><subfield code="0">(DE-588)4213132-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</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">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=" "><subfield code="a">Electronic books</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Data Mining</subfield><subfield code="0">(DE-588)4428654-5</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">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="4"><subfield code="a">Vorhersagetheorie</subfield><subfield code="0">(DE-588)4188671-9</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="5"><subfield code="a">Datenmodell</subfield><subfield code="0">(DE-588)4192516-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="6"><subfield code="a">Datenmanagement</subfield><subfield code="0">(DE-588)4213132-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="7"><subfield code="a">Prognose</subfield><subfield code="0">(DE-588)4047390-9</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chaouchi, Mohamed</subfield><subfield code="e">Sonstige</subfield><subfield code="0">(DE-588)1050253884</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jung, Tommy</subfield><subfield code="e">Sonstige</subfield><subfield code="0">(DE-588)1050253949</subfield><subfield code="4">oth</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">978-1-118-72896-3</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=714691</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-NLEBK</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027432902</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=714691</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-4-NLEBK</subfield><subfield code="q">TUM_PDA_EBSCO_BAE_gekauft</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV041990654 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:10:01Z |
| institution | BVB |
| isbn | 111872920X 1118729412 9781118729205 9781118729410 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027432902 |
| oclc_num | 864560209 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (xii, 348 p.) |
| psigel | ZDB-4-NLEBK ZDB-4-NLEBK TUM_PDA_EBSCO_BAE_gekauft |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Wiley |
| record_format | marc |
| series2 | --For dummies |
| spelling | Bari, Anasse Verfasser (DE-588)1050253795 aut Predictive analytics for dummies Anasse Bari, Mohamed Chaouchi, and Tommy Jung Hoboken, N.J. Wiley 2014 1 Online-Ressource (xii, 348 p.) txt rdacontent c rdamedia cr rdacarrier --For dummies Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big DataPredictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businessesHelps readers see how to shepherd predictive analytics projects through their companiesExplains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and moreCovers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing dataAlso covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewherePropose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies BUSINESS & ECONOMICS / New Business Enterprises bisacsh BUSINESS & ECONOMICS / Industrial Management bisacsh BUSINESS & ECONOMICS / Management bisacsh BUSINESS & ECONOMICS / Management Science bisacsh BUSINESS & ECONOMICS / Organizational Behavior bisacsh Datenverarbeitung Mathematisches Modell Wirtschaft Management / Data processing Management / Mathematical models Data mining Prognose (DE-588)4047390-9 gnd rswk-swf Vorhersagetheorie (DE-588)4188671-9 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Datenmodell (DE-588)4192516-6 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Datenmanagement (DE-588)4213132-7 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Electronic books Data Mining (DE-588)4428654-5 s Datenanalyse (DE-588)4123037-1 s Maschinelles Lernen (DE-588)4193754-5 s Big Data (DE-588)4802620-7 s Vorhersagetheorie (DE-588)4188671-9 s Datenmodell (DE-588)4192516-6 s Datenmanagement (DE-588)4213132-7 s Prognose (DE-588)4047390-9 s 1\p DE-604 Chaouchi, Mohamed Sonstige (DE-588)1050253884 oth Jung, Tommy Sonstige (DE-588)1050253949 oth Erscheint auch als Druck-Ausgabe, Paperback 978-1-118-72896-3 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=714691 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Bari, Anasse Predictive analytics for dummies BUSINESS & ECONOMICS / New Business Enterprises bisacsh BUSINESS & ECONOMICS / Industrial Management bisacsh BUSINESS & ECONOMICS / Management bisacsh BUSINESS & ECONOMICS / Management Science bisacsh BUSINESS & ECONOMICS / Organizational Behavior bisacsh Datenverarbeitung Mathematisches Modell Wirtschaft Management / Data processing Management / Mathematical models Data mining Prognose (DE-588)4047390-9 gnd Vorhersagetheorie (DE-588)4188671-9 gnd Data Mining (DE-588)4428654-5 gnd Datenmodell (DE-588)4192516-6 gnd Big Data (DE-588)4802620-7 gnd Datenmanagement (DE-588)4213132-7 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Datenanalyse (DE-588)4123037-1 gnd |
| subject_GND | (DE-588)4047390-9 (DE-588)4188671-9 (DE-588)4428654-5 (DE-588)4192516-6 (DE-588)4802620-7 (DE-588)4213132-7 (DE-588)4193754-5 (DE-588)4123037-1 |
| title | Predictive analytics for dummies |
| title_auth | Predictive analytics for dummies |
| title_exact_search | Predictive analytics for dummies |
| title_full | Predictive analytics for dummies Anasse Bari, Mohamed Chaouchi, and Tommy Jung |
| title_fullStr | Predictive analytics for dummies Anasse Bari, Mohamed Chaouchi, and Tommy Jung |
| title_full_unstemmed | Predictive analytics for dummies Anasse Bari, Mohamed Chaouchi, and Tommy Jung |
| title_short | Predictive analytics for dummies |
| title_sort | predictive analytics for dummies |
| topic | BUSINESS & ECONOMICS / New Business Enterprises bisacsh BUSINESS & ECONOMICS / Industrial Management bisacsh BUSINESS & ECONOMICS / Management bisacsh BUSINESS & ECONOMICS / Management Science bisacsh BUSINESS & ECONOMICS / Organizational Behavior bisacsh Datenverarbeitung Mathematisches Modell Wirtschaft Management / Data processing Management / Mathematical models Data mining Prognose (DE-588)4047390-9 gnd Vorhersagetheorie (DE-588)4188671-9 gnd Data Mining (DE-588)4428654-5 gnd Datenmodell (DE-588)4192516-6 gnd Big Data (DE-588)4802620-7 gnd Datenmanagement (DE-588)4213132-7 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Datenanalyse (DE-588)4123037-1 gnd |
| topic_facet | BUSINESS & ECONOMICS / New Business Enterprises BUSINESS & ECONOMICS / Industrial Management BUSINESS & ECONOMICS / Management BUSINESS & ECONOMICS / Management Science BUSINESS & ECONOMICS / Organizational Behavior Datenverarbeitung Mathematisches Modell Wirtschaft Management / Data processing Management / Mathematical models Data mining Prognose Vorhersagetheorie Data Mining Datenmodell Big Data Datenmanagement Maschinelles Lernen Datenanalyse |
| url | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=714691 |
| work_keys_str_mv | AT barianasse predictiveanalyticsfordummies AT chaouchimohamed predictiveanalyticsfordummies AT jungtommy predictiveanalyticsfordummies |