Applied supervised learning with Python :: use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning /
Applied Supervised Learning with Python provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this book, you'll learn Jupyter Notebooks, the technology used in academic and c...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing Ltd,
2019.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Applied Supervised Learning with Python provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this book, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support. |
| Beschreibung: | 1 online resource |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 1789955831 9781789955835 |
Internformat
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBA-on1101039206 | ||
| 003 | OCoLC | ||
| 005 | 20241004212047.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 190511t20192019enk ob 001 0 eng d | ||
| 040 | |a EBLCP |b eng |e rda |e pn |c EBLCP |d YDX |d YDXIT |d UKAHL |d A7U |d UKMGB |d OCLCF |d OCLCQ |d N$T |d OCLCQ |d UMI |d NLW |d OCLCQ |d OCLCO |d KSU |d Z5A |d OCLCQ |d OCLCO | ||
| 015 | |a GBB995128 |2 bnb | ||
| 016 | 7 | |a 019397912 |2 Uk | |
| 019 | |a 1099949953 |a 1226354939 | ||
| 020 | |a 1789955831 |q (electronic book) | ||
| 020 | |a 9781789955835 |q (electronic bk.) | ||
| 020 | |z 9781789954920 | ||
| 035 | |a (OCoLC)1101039206 |z (OCoLC)1099949953 |z (OCoLC)1226354939 | ||
| 037 | |a 9781789955835 |b Packt Publishing | ||
| 050 | 4 | |a QA76.73.P98 |b J64 2019 | |
| 082 | 7 | |a 005.13/3 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Johnston, Benjamin, |e author. | |
| 245 | 1 | 0 | |a Applied supervised learning with Python : |b use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / |c Benjamin Johnston and Ishita Mathur. |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing Ltd, |c 2019. | |
| 264 | 4 | |c ©2019 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 505 | 0 | 0 | |g 1. |t Python Machine Learning Toolkit -- |g 2. |t Exploratory Data Analysis and Visualization -- |g 3. |t Regression Analysis -- |g 4. |t Classification -- |g 5. |t Ensemble Modeling -- |g 6. |t Model Evaluation. |
| 520 | |a Applied Supervised Learning with Python provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this book, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support. | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on May 15, 2019). | |
| 504 | |a Includes bibliographical references and index. | ||
| 650 | 0 | |a Python (Computer program language) |0 http://id.loc.gov/authorities/subjects/sh96008834 | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 700 | 1 | |a Mathur, Ishita, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Johnston, Benjamin. |t Applied Supervised Learning with Python : Use Scikit-Learn to Build Predictive Models from Real-world Datasets and Prepare Yourself for the Future of Machine Learning. |d Birmingham : Packt Publishing, Limited, ©2019 |z 9781789954920 |
| 856 | 4 | 0 | |l FWS01 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2112649 |3 Volltext |
| 938 | |a Askews and Holts Library Services |b ASKH |n BDZ0040025735 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5763194 | ||
| 938 | |a EBSCOhost |b EBSC |n 2112649 | ||
| 938 | |a YBP Library Services |b YANK |n 300501277 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBA | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-on1101039206 |
|---|---|
| _version_ | 1816882492431400960 |
| adam_text | |
| any_adam_object | |
| author | Johnston, Benjamin Mathur, Ishita |
| author_facet | Johnston, Benjamin Mathur, Ishita |
| author_role | aut aut |
| author_sort | Johnston, Benjamin |
| author_variant | b j bj i m im |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.73.P98 J64 2019 |
| callnumber-search | QA76.73.P98 J64 2019 |
| callnumber-sort | QA 276.73 P98 J64 42019 |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-4-EBA |
| contents | Python Machine Learning Toolkit -- Exploratory Data Analysis and Visualization -- Regression Analysis -- Classification -- Ensemble Modeling -- Model Evaluation. |
| ctrlnum | (OCoLC)1101039206 |
| dewey-full | 005.13/3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.13/3 |
| dewey-search | 005.13/3 |
| dewey-sort | 15.13 13 |
| 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>02907cam a2200517 i 4500</leader><controlfield tag="001">ZDB-4-EBA-on1101039206</controlfield><controlfield tag="003">OCoLC</controlfield><controlfield tag="005">20241004212047.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr cnu---unuuu</controlfield><controlfield tag="008">190511t20192019enk ob 001 0 eng d</controlfield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">EBLCP</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">EBLCP</subfield><subfield code="d">YDX</subfield><subfield code="d">YDXIT</subfield><subfield code="d">UKAHL</subfield><subfield code="d">A7U</subfield><subfield code="d">UKMGB</subfield><subfield code="d">OCLCF</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">N$T</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">UMI</subfield><subfield code="d">NLW</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">KSU</subfield><subfield code="d">Z5A</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield></datafield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">GBB995128</subfield><subfield code="2">bnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">019397912</subfield><subfield code="2">Uk</subfield></datafield><datafield tag="019" ind1=" " ind2=" "><subfield code="a">1099949953</subfield><subfield code="a">1226354939</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1789955831</subfield><subfield code="q">(electronic book)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781789955835</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781789954920</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1101039206</subfield><subfield code="z">(OCoLC)1099949953</subfield><subfield code="z">(OCoLC)1226354939</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">9781789955835</subfield><subfield code="b">Packt Publishing</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA76.73.P98</subfield><subfield code="b">J64 2019</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">005.13/3</subfield><subfield code="2">23</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">MAIN</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Johnston, Benjamin,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Applied supervised learning with Python :</subfield><subfield code="b">use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning /</subfield><subfield code="c">Benjamin Johnston and Ishita Mathur.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK :</subfield><subfield code="b">Packt Publishing Ltd,</subfield><subfield code="c">2019.</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2019</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="505" ind1="0" ind2="0"><subfield code="g">1.</subfield><subfield code="t">Python Machine Learning Toolkit --</subfield><subfield code="g">2.</subfield><subfield code="t">Exploratory Data Analysis and Visualization --</subfield><subfield code="g">3.</subfield><subfield code="t">Regression Analysis --</subfield><subfield code="g">4.</subfield><subfield code="t">Classification --</subfield><subfield code="g">5.</subfield><subfield code="t">Ensemble Modeling --</subfield><subfield code="g">6.</subfield><subfield code="t">Model Evaluation.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Applied Supervised Learning with Python provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this book, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support.</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Online resource; title from digital title page (viewed on May 15, 2019).</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Python (Computer program language)</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh96008834</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Python (Langage de programmation)</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Python (Computer program language)</subfield><subfield code="2">fast</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mathur, Ishita,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="a">Johnston, Benjamin.</subfield><subfield code="t">Applied Supervised Learning with Python : Use Scikit-Learn to Build Predictive Models from Real-world Datasets and Prepare Yourself for the Future of Machine Learning.</subfield><subfield code="d">Birmingham : Packt Publishing, Limited, ©2019</subfield><subfield code="z">9781789954920</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">FWS01</subfield><subfield code="p">ZDB-4-EBA</subfield><subfield code="q">FWS_PDA_EBA</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2112649</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">Askews and Holts Library Services</subfield><subfield code="b">ASKH</subfield><subfield code="n">BDZ0040025735</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">ProQuest Ebook Central</subfield><subfield code="b">EBLB</subfield><subfield code="n">EBL5763194</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">2112649</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">YBP Library Services</subfield><subfield code="b">YANK</subfield><subfield code="n">300501277</subfield></datafield><datafield tag="994" ind1=" " ind2=" "><subfield code="a">92</subfield><subfield code="b">GEBAY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-EBA</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-4-EBA-on1101039206 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:29:28Z |
| institution | BVB |
| isbn | 1789955831 9781789955835 |
| language | English |
| oclc_num | 1101039206 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource |
| psigel | ZDB-4-EBA |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Packt Publishing Ltd, |
| record_format | marc |
| spelling | Johnston, Benjamin, author. Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / Benjamin Johnston and Ishita Mathur. Birmingham, UK : Packt Publishing Ltd, 2019. ©2019 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier 1. Python Machine Learning Toolkit -- 2. Exploratory Data Analysis and Visualization -- 3. Regression Analysis -- 4. Classification -- 5. Ensemble Modeling -- 6. Model Evaluation. Applied Supervised Learning with Python provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this book, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support. Online resource; title from digital title page (viewed on May 15, 2019). Includes bibliographical references and index. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Python (Langage de programmation) Python (Computer program language) fast Mathur, Ishita, author. Print version: Johnston, Benjamin. Applied Supervised Learning with Python : Use Scikit-Learn to Build Predictive Models from Real-world Datasets and Prepare Yourself for the Future of Machine Learning. Birmingham : Packt Publishing, Limited, ©2019 9781789954920 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2112649 Volltext |
| spellingShingle | Johnston, Benjamin Mathur, Ishita Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / Python Machine Learning Toolkit -- Exploratory Data Analysis and Visualization -- Regression Analysis -- Classification -- Ensemble Modeling -- Model Evaluation. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Python (Langage de programmation) Python (Computer program language) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh96008834 |
| title | Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / |
| title_alt | Python Machine Learning Toolkit -- Exploratory Data Analysis and Visualization -- Regression Analysis -- Classification -- Ensemble Modeling -- Model Evaluation. |
| title_auth | Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / |
| title_exact_search | Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / |
| title_full | Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / Benjamin Johnston and Ishita Mathur. |
| title_fullStr | Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / Benjamin Johnston and Ishita Mathur. |
| title_full_unstemmed | Applied supervised learning with Python : use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / Benjamin Johnston and Ishita Mathur. |
| title_short | Applied supervised learning with Python : |
| title_sort | applied supervised learning with python use scikit learn to build predictive models from real world datasets and prepare yourself for the future of machine learning |
| title_sub | use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning / |
| topic | Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Python (Langage de programmation) Python (Computer program language) fast |
| topic_facet | Python (Computer program language) Python (Langage de programmation) |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2112649 |
| work_keys_str_mv | AT johnstonbenjamin appliedsupervisedlearningwithpythonusescikitlearntobuildpredictivemodelsfromrealworlddatasetsandprepareyourselfforthefutureofmachinelearning AT mathurishita appliedsupervisedlearningwithpythonusescikitlearntobuildpredictivemodelsfromrealworlddatasetsandprepareyourselfforthefutureofmachinelearning |