Machine learning in Python: essential techniques for predictive analysis
Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively pr...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Indianapolis, IN
Wiley
[2015]
|
Schlagworte: | |
Online-Zugang: | BFB01 FCO01 FHI01 FHN01 FLA01 FRO01 FUBA1 FWS01 FWS02 TUM01 UBM01 UBT01 UBY01 Volltext |
Zusammenfassung: | Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or sta |
Beschreibung: | 1 Online-Ressource (xxix, 319 Seiten) |
ISBN: | 9781119183600 9781118961766 9781118961759 |
Internformat
MARC
LEADER | 00000nmm a2200000 c 4500 | ||
---|---|---|---|
001 | BV043397686 | ||
003 | DE-604 | ||
005 | 20240215 | ||
007 | cr|uuu---uuuuu | ||
008 | 160222s2015 |||| o||u| ||||||eng d | ||
020 | |a 9781119183600 |c electronic bk |9 978-1-119-18360-0 | ||
020 | |a 9781118961766 |c electronic bk |9 978-1-118-96176-6 | ||
020 | |a 9781118961759 |c electronic bk |9 978-1-118-96175-9 | ||
024 | 7 | |a 10.1002/9781119183600 |2 doi | |
035 | |a (ZDB-35-WIC)ocn906699047 | ||
035 | |a (ZDB-30-PQE)EBC1895171 | ||
035 | |a (ZDB-89-EBL)EBL1895171 | ||
035 | |a (ZDB-38-EBR)ebr11041441 | ||
035 | |a (OCoLC)906699047 | ||
035 | |a (DE-599)BVBBV043397686 | ||
040 | |a DE-604 |b ger |e rda | ||
041 | 0 | |a eng | |
049 | |a DE-91 |a DE-573 |a DE-860 |a DE-863 |a DE-862 |a DE-92 |a DE-861 |a DE-706 |a DE-19 |a DE-703 |a DE-188 |a DE-522 |a DE-858 | ||
082 | 0 | |a 006.31 |2 23 | |
084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
100 | 1 | |a Bowles, Michael |e Verfasser |0 (DE-588)1074267184 |4 aut | |
245 | 1 | 0 | |a Machine learning in Python |b essential techniques for predictive analysis |c Michael Bowles |
264 | 1 | |a Indianapolis, IN |b Wiley |c [2015] | |
264 | 4 | |c © 2015 | |
300 | |a 1 Online-Ressource (xxix, 319 Seiten) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
520 | |a Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or sta | ||
650 | 7 | |a COMPUTERS / General |2 bisacsh | |
650 | 7 | |a Machine learning |2 fast | |
650 | 7 | |a Python (Computer program language) |2 fast | |
650 | 4 | |a Machine learning | |
650 | 4 | |a Python (Computer program language) | |
650 | 0 | 7 | |a Python |g Programmiersprache |0 (DE-588)4434275-5 |2 gnd |9 rswk-swf |
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 | 1 | |a Python |g Programmiersprache |0 (DE-588)4434275-5 |D s |
689 | 0 | |5 DE-604 | |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-118-96174-2 |a Bowles, Michael |t Machine Learning in Python : Essential Techniques for Predictive Analysis |
856 | 4 | 0 | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
912 | |a ZDB-35-WIC |a ZDB-30-PQE | ||
999 | |a oai:aleph.bib-bvb.de:BVB01-028816270 | ||
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l BFB01 |p ZDB-35-WEL |q BFB_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FCO01 |p ZDB-35-WIC |q FCO_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FHI01 |p ZDB-35-WIC |q FHI_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FHN01 |p ZDB-35-WIC |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FLA01 |p ZDB-35-WIC |q FLA_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FRO01 |p ZDB-35-WIC |q FRO_PDA_WIC |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FUBA1 |p ZDB-35-WIC |q ZDB-35-WIC 2017 |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FWS01 |p ZDB-35-WIC |q FWS_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l FWS02 |p ZDB-35-WIC |q FWS_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l TUM01 |p ZDB-35-WIC |q TUM_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l UBM01 |p ZDB-35-WIC |q UBM_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l UBT01 |p ZDB-35-WIC |q UBT_PDA_WIC_Kauf |x Verlag |3 Volltext | |
966 | e | |u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |l UBY01 |p ZDB-35-WIC |q UBY_PDA_WIC_Kauf |x Verlag |3 Volltext |
Datensatz im Suchindex
DE-BY-FWS_katkey | 611519 |
---|---|
_version_ | 1806179670809378816 |
any_adam_object | |
author | Bowles, Michael |
author_GND | (DE-588)1074267184 |
author_facet | Bowles, Michael |
author_role | aut |
author_sort | Bowles, Michael |
author_variant | m b mb |
building | Verbundindex |
bvnumber | BV043397686 |
classification_rvk | ST 300 |
collection | ZDB-35-WIC ZDB-30-PQE |
ctrlnum | (ZDB-35-WIC)ocn906699047 (ZDB-30-PQE)EBC1895171 (ZDB-89-EBL)EBL1895171 (ZDB-38-EBR)ebr11041441 (OCoLC)906699047 (DE-599)BVBBV043397686 |
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>05851nmm a2200697 c 4500</leader><controlfield tag="001">BV043397686</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240215 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">160222s2015 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119183600</subfield><subfield code="c">electronic bk</subfield><subfield code="9">978-1-119-18360-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781118961766</subfield><subfield code="c">electronic bk</subfield><subfield code="9">978-1-118-96176-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781118961759</subfield><subfield code="c">electronic bk</subfield><subfield code="9">978-1-118-96175-9</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/9781119183600</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-35-WIC)ocn906699047</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC1895171</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL1895171</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-38-EBR)ebr11041441</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)906699047</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043397686</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><subfield code="a">DE-573</subfield><subfield code="a">DE-860</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-862</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-861</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-188</subfield><subfield code="a">DE-522</subfield><subfield code="a">DE-858</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.31</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="100" ind1="1" ind2=" "><subfield code="a">Bowles, Michael</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1074267184</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Machine learning in Python</subfield><subfield code="b">essential techniques for predictive analysis</subfield><subfield code="c">Michael Bowles</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Indianapolis, IN</subfield><subfield code="b">Wiley</subfield><subfield code="c">[2015]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2015</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xxix, 319 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">Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or sta</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">COMPUTERS / General</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Python (Computer program language)</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Python</subfield><subfield code="g">Programmiersprache</subfield><subfield code="0">(DE-588)4434275-5</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="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">Python</subfield><subfield code="g">Programmiersprache</subfield><subfield code="0">(DE-588)4434275-5</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</subfield><subfield code="z">978-1-118-96174-2</subfield><subfield code="a">Bowles, Michael</subfield><subfield code="t">Machine Learning in Python : Essential Techniques for Predictive Analysis</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</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-35-WIC</subfield><subfield code="a">ZDB-30-PQE</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-028816270</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">BFB01</subfield><subfield code="p">ZDB-35-WEL</subfield><subfield code="q">BFB_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FCO01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">FCO_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FHI01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">FHI_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FLA01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">FLA_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FRO01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">FRO_PDA_WIC</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FUBA1</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">ZDB-35-WIC 2017</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FWS01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">FWS_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">FWS02</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">FWS_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">TUM_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">UBM01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">UBM_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">UBT01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">UBT_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-35-WIC</subfield><subfield code="q">UBY_PDA_WIC_Kauf</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
id | DE-604.BV043397686 |
illustrated | Not Illustrated |
indexdate | 2024-08-01T12:12:42Z |
institution | BVB |
isbn | 9781119183600 9781118961766 9781118961759 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028816270 |
oclc_num | 906699047 |
open_access_boolean | |
owner | DE-91 DE-BY-TUM DE-573 DE-860 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-92 DE-861 DE-706 DE-19 DE-BY-UBM DE-703 DE-188 DE-522 DE-858 |
owner_facet | DE-91 DE-BY-TUM DE-573 DE-860 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-92 DE-861 DE-706 DE-19 DE-BY-UBM DE-703 DE-188 DE-522 DE-858 |
physical | 1 Online-Ressource (xxix, 319 Seiten) |
psigel | ZDB-35-WIC ZDB-30-PQE ZDB-35-WEL BFB_Kauf ZDB-35-WIC FCO_PDA_WIC_Kauf ZDB-35-WIC FHI_PDA_WIC_Kauf ZDB-35-WIC FLA_PDA_WIC_Kauf ZDB-35-WIC FRO_PDA_WIC ZDB-35-WIC ZDB-35-WIC 2017 ZDB-35-WIC FWS_PDA_WIC_Kauf ZDB-35-WIC TUM_PDA_WIC_Kauf ZDB-35-WIC UBM_PDA_WIC_Kauf ZDB-35-WIC UBT_PDA_WIC_Kauf ZDB-35-WIC UBY_PDA_WIC_Kauf |
publishDate | 2015 |
publishDateSearch | 2015 |
publishDateSort | 2015 |
publisher | Wiley |
record_format | marc |
spellingShingle | Bowles, Michael Machine learning in Python essential techniques for predictive analysis COMPUTERS / General bisacsh Machine learning fast Python (Computer program language) fast Machine learning Python (Computer program language) Python Programmiersprache (DE-588)4434275-5 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
subject_GND | (DE-588)4434275-5 (DE-588)4193754-5 |
title | Machine learning in Python essential techniques for predictive analysis |
title_auth | Machine learning in Python essential techniques for predictive analysis |
title_exact_search | Machine learning in Python essential techniques for predictive analysis |
title_full | Machine learning in Python essential techniques for predictive analysis Michael Bowles |
title_fullStr | Machine learning in Python essential techniques for predictive analysis Michael Bowles |
title_full_unstemmed | Machine learning in Python essential techniques for predictive analysis Michael Bowles |
title_short | Machine learning in Python |
title_sort | machine learning in python essential techniques for predictive analysis |
title_sub | essential techniques for predictive analysis |
topic | COMPUTERS / General bisacsh Machine learning fast Python (Computer program language) fast Machine learning Python (Computer program language) Python Programmiersprache (DE-588)4434275-5 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
topic_facet | COMPUTERS / General Machine learning Python (Computer program language) Python Programmiersprache Maschinelles Lernen |
url | https://onlinelibrary.wiley.com/doi/book/10.1002/9781119183600 |
work_keys_str_mv | AT bowlesmichael machinelearninginpythonessentialtechniquesforpredictiveanalysis |