Python :: deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules.
Leverage benefits of machine learning techniques using Python. About This Book Improve and optimise machine learning systems using effective strategies. Develop a strategy to deal with a large amount of data. Use of Python code for implementing a range of machine learning algorithms and techniques....
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2016.
|
| Schriftenreihe: | Learning path.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Leverage benefits of machine learning techniques using Python. About This Book Improve and optimise machine learning systems using effective strategies. Develop a strategy to deal with a large amount of data. Use of Python code for implementing a range of machine learning algorithms and techniques. Who This Book Is For This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts. What You Will Learn Learn to write clean and elegant Python code that will optimize the strength of your algorithms Uncover hidden patterns and structures in data with clustering Improve accuracy and consistency of results using powerful feature engineering techniques Gain practical and theoretical understanding of cutting-edge deep learning algorithms Solve unique tasks by building models Get grips on the machine learning design process In Detail Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems. The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems. At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering. Style and approach This course includes all the resource... |
| Beschreibung: | Authors: Sebastian Raschka, David Julian, John Hearty. Cf. Credits page. |
| Beschreibung: | 1 online resource (1 volume) : illustrations. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781787128545 1787128547 9781787128576 1787128571 |
Internformat
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBA-ocn959736342 | ||
| 003 | OCoLC | ||
| 005 | 20241004212047.0 | ||
| 006 | m o d | ||
| 007 | cr unu|||||||| | ||
| 008 | 161003s2016 enka ob 001 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d TOH |d STF |d OCLCF |d IDEBK |d YDX |d N$T |d OCLCQ |d DEBBG |d OCLCQ |d VT2 |d UOK |d CEF |d KSU |d UKMGB |d WYU |d ZCU |d AGLDB |d IGB |d UKAHL |d QGK |d OCLCO |d OCLCQ |d OCLCO |d OCLCL |d OCLCQ | ||
| 015 | |a GBB6J3291 |2 bnb | ||
| 016 | 7 | |a 018073200 |2 Uk | |
| 019 | |a 958085587 |a 958120970 |a 1062334392 | ||
| 020 | |a 9781787128545 | ||
| 020 | |a 1787128547 | ||
| 020 | |a 9781787128576 | ||
| 020 | |a 1787128571 | ||
| 035 | |a (OCoLC)959736342 |z (OCoLC)958085587 |z (OCoLC)958120970 |z (OCoLC)1062334392 | ||
| 037 | |a CL0500000788 |b Safari Books Online | ||
| 050 | 4 | |a Q325.5 | |
| 072 | 7 | |a COM |x 000000 |2 bisacsh | |
| 082 | 7 | |a 006.31 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Raschka, Sebastian, |e author. |0 http://id.loc.gov/authorities/names/no2016023528 | |
| 245 | 1 | 0 | |a Python : |b deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2016. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Learning path | |
| 588 | 0 | |a Online resource; title from title page (Safari, viewed October 3, 2016). | |
| 500 | |a Authors: Sebastian Raschka, David Julian, John Hearty. Cf. Credits page. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a Leverage benefits of machine learning techniques using Python. About This Book Improve and optimise machine learning systems using effective strategies. Develop a strategy to deal with a large amount of data. Use of Python code for implementing a range of machine learning algorithms and techniques. Who This Book Is For This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts. What You Will Learn Learn to write clean and elegant Python code that will optimize the strength of your algorithms Uncover hidden patterns and structures in data with clustering Improve accuracy and consistency of results using powerful feature engineering techniques Gain practical and theoretical understanding of cutting-edge deep learning algorithms Solve unique tasks by building models Get grips on the machine learning design process In Detail Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems. The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems. At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering. Style and approach This course includes all the resource... | ||
| 650 | 0 | |a Machine learning. |0 http://id.loc.gov/authorities/subjects/sh85079324 | |
| 650 | 0 | |a Python (Computer program language) |0 http://id.loc.gov/authorities/subjects/sh96008834 | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 700 | 1 | |a Julian, David, |e author. | |
| 700 | 1 | |a Hearty, John, |e author. | |
| 776 | 0 | 8 | |i Print version: |t Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |d Birmingham, England ; Mumbai, [India] : Packt Publishing, c2016 |h vii, 881 pages |z 9781787128576 |
| 830 | 0 | |a Learning path. |0 http://id.loc.gov/authorities/names/no2018038408 | |
| 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=1345206 |3 Volltext |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH31620689 | ||
| 938 | |a EBSCOhost |b EBSC |n 1345206 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis35760766 | ||
| 938 | |a YBP Library Services |b YANK |n 13150729 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBA | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-ocn959736342 |
|---|---|
| _version_ | 1816882363845574656 |
| adam_text | |
| any_adam_object | |
| author | Raschka, Sebastian Julian, David Hearty, John |
| author_GND | http://id.loc.gov/authorities/names/no2016023528 |
| author_facet | Raschka, Sebastian Julian, David Hearty, John |
| author_role | aut aut aut |
| author_sort | Raschka, Sebastian |
| author_variant | s r sr d j dj j h jh |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | Q325 |
| callnumber-raw | Q325.5 |
| callnumber-search | Q325.5 |
| callnumber-sort | Q 3325.5 |
| callnumber-subject | Q - General Science |
| collection | ZDB-4-EBA |
| ctrlnum | (OCoLC)959736342 |
| 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>05361cam a2200613 i 4500</leader><controlfield tag="001">ZDB-4-EBA-ocn959736342</controlfield><controlfield tag="003">OCoLC</controlfield><controlfield tag="005">20241004212047.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr unu||||||||</controlfield><controlfield tag="008">161003s2016 enka ob 001 0 eng d</controlfield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">UMI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">UMI</subfield><subfield code="d">TOH</subfield><subfield code="d">STF</subfield><subfield code="d">OCLCF</subfield><subfield code="d">IDEBK</subfield><subfield code="d">YDX</subfield><subfield code="d">N$T</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">DEBBG</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">VT2</subfield><subfield code="d">UOK</subfield><subfield code="d">CEF</subfield><subfield code="d">KSU</subfield><subfield code="d">UKMGB</subfield><subfield code="d">WYU</subfield><subfield code="d">ZCU</subfield><subfield code="d">AGLDB</subfield><subfield code="d">IGB</subfield><subfield code="d">UKAHL</subfield><subfield code="d">QGK</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCL</subfield><subfield code="d">OCLCQ</subfield></datafield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">GBB6J3291</subfield><subfield code="2">bnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">018073200</subfield><subfield code="2">Uk</subfield></datafield><datafield tag="019" ind1=" " ind2=" "><subfield code="a">958085587</subfield><subfield code="a">958120970</subfield><subfield code="a">1062334392</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781787128545</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1787128547</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781787128576</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1787128571</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)959736342</subfield><subfield code="z">(OCoLC)958085587</subfield><subfield code="z">(OCoLC)958120970</subfield><subfield code="z">(OCoLC)1062334392</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">CL0500000788</subfield><subfield code="b">Safari Books Online</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">Q325.5</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM</subfield><subfield code="x">000000</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">006.31</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">Raschka, Sebastian,</subfield><subfield code="e">author.</subfield><subfield code="0">http://id.loc.gov/authorities/names/no2016023528</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Python :</subfield><subfield code="b">deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK :</subfield><subfield code="b">Packt Publishing,</subfield><subfield code="c">2016.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (1 volume) :</subfield><subfield code="b">illustrations.</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="490" ind1="1" ind2=" "><subfield code="a">Learning path</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Online resource; title from title page (Safari, viewed October 3, 2016).</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Authors: Sebastian Raschka, David Julian, John Hearty. Cf. Credits page.</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Leverage benefits of machine learning techniques using Python. About This Book Improve and optimise machine learning systems using effective strategies. Develop a strategy to deal with a large amount of data. Use of Python code for implementing a range of machine learning algorithms and techniques. Who This Book Is For This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts. What You Will Learn Learn to write clean and elegant Python code that will optimize the strength of your algorithms Uncover hidden patterns and structures in data with clustering Improve accuracy and consistency of results using powerful feature engineering techniques Gain practical and theoretical understanding of cutting-edge deep learning algorithms Solve unique tasks by building models Get grips on the machine learning design process In Detail Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems. The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems. At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering. Style and approach This course includes all the resource...</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh85079324</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">Apprentissage automatique.</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">COMPUTERS</subfield><subfield code="x">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="700" ind1="1" ind2=" "><subfield code="a">Julian, David,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hearty, John,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="t">Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules.</subfield><subfield code="d">Birmingham, England ; Mumbai, [India] : Packt Publishing, c2016</subfield><subfield code="h">vii, 881 pages</subfield><subfield code="z">9781787128576</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Learning path.</subfield><subfield code="0">http://id.loc.gov/authorities/names/no2018038408</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=1345206</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">AH31620689</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">1345206</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">ProQuest MyiLibrary Digital eBook Collection</subfield><subfield code="b">IDEB</subfield><subfield code="n">cis35760766</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">YBP Library Services</subfield><subfield code="b">YANK</subfield><subfield code="n">13150729</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-ocn959736342 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:27:26Z |
| institution | BVB |
| isbn | 9781787128545 1787128547 9781787128576 1787128571 |
| language | English |
| oclc_num | 959736342 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (1 volume) : illustrations. |
| psigel | ZDB-4-EBA |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | Packt Publishing, |
| record_format | marc |
| series | Learning path. |
| series2 | Learning path |
| spelling | Raschka, Sebastian, author. http://id.loc.gov/authorities/names/no2016023528 Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. Birmingham, UK : Packt Publishing, 2016. 1 online resource (1 volume) : illustrations. text txt rdacontent computer c rdamedia online resource cr rdacarrier Learning path Online resource; title from title page (Safari, viewed October 3, 2016). Authors: Sebastian Raschka, David Julian, John Hearty. Cf. Credits page. Includes bibliographical references and index. Leverage benefits of machine learning techniques using Python. About This Book Improve and optimise machine learning systems using effective strategies. Develop a strategy to deal with a large amount of data. Use of Python code for implementing a range of machine learning algorithms and techniques. Who This Book Is For This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts. What You Will Learn Learn to write clean and elegant Python code that will optimize the strength of your algorithms Uncover hidden patterns and structures in data with clustering Improve accuracy and consistency of results using powerful feature engineering techniques Gain practical and theoretical understanding of cutting-edge deep learning algorithms Solve unique tasks by building models Get grips on the machine learning design process In Detail Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems. The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems. At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering. Style and approach This course includes all the resource... Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Apprentissage automatique. Python (Langage de programmation) COMPUTERS General. bisacsh Machine learning fast Python (Computer program language) fast Julian, David, author. Hearty, John, author. Print version: Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. Birmingham, England ; Mumbai, [India] : Packt Publishing, c2016 vii, 881 pages 9781787128576 Learning path. http://id.loc.gov/authorities/names/no2018038408 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1345206 Volltext |
| spellingShingle | Raschka, Sebastian Julian, David Hearty, John Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. Learning path. Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Apprentissage automatique. Python (Langage de programmation) COMPUTERS General. bisacsh Machine learning fast Python (Computer program language) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh96008834 |
| title | Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| title_auth | Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| title_exact_search | Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| title_full | Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| title_fullStr | Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| title_full_unstemmed | Python : deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| title_short | Python : |
| title_sort | python deeper insights into machine learning leverage benefits of machine learning techniques using python a course in three modules |
| title_sub | deeper insights into machine learning : leverage benefits of machine learning techniques using Python : a course in three modules. |
| topic | Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Apprentissage automatique. Python (Langage de programmation) COMPUTERS General. bisacsh Machine learning fast Python (Computer program language) fast |
| topic_facet | Machine learning. Python (Computer program language) Apprentissage automatique. Python (Langage de programmation) COMPUTERS General. Machine learning |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1345206 |
| work_keys_str_mv | AT raschkasebastian pythondeeperinsightsintomachinelearningleveragebenefitsofmachinelearningtechniquesusingpythonacourseinthreemodules AT juliandavid pythondeeperinsightsintomachinelearningleveragebenefitsofmachinelearningtechniquesusingpythonacourseinthreemodules AT heartyjohn pythondeeperinsightsintomachinelearningleveragebenefitsofmachinelearningtechniquesusingpythonacourseinthreemodules |