Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/934
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dc.contributor.authorHaroon, Danish. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:34Z-
dc.date.available2020-05-17T08:23:34Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484228234 ;en_US
dc.identifier.isbn9781484228227 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/934-
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484228227. ;en_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractEmbrace machine learning approaches and Python to enable automatic rendering of rich insights. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Studyetakes you through the steps to improve business processes and determine the pivotal points that frame strategies. Youeell see machine learning techniques that you can use to support your products and services. Moreover youeell learn the pros and cons of each of the machine learning concepts presented. By taking a step-by-step approach to coding in Python youeell be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure th at you understand the data science approach to solving real-world problems. You will: Gain insights into machine learning conceptse Work on real-world applications of machine learning Get a hands-on overview to Python from a machine learning point of view. ;en_US
dc.description.statementofresponsibilityby Danish Haroon.en_US
dc.description.tableofcontentsChapter 1: eStatistics and Probability -- Chapter 2: eRegression -- Chapter 3: Time series models -- Chapter 4: Classification and Clustering -- Chapter 5: Ensemble methods. ;en_US
dc.format.extentXVII, 204 p. 120 illus., 99 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484228234.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputer Programmingen_US
dc.subjectProgramming Languages and Electronic Computersen_US
dc.subjectDatabase Managementen_US
dc.subjectComputersen_US
dc.subjectComputer Scienceen_US
dc.subjectComputing Methodologies. ;en_US
dc.subjectPython. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectProgramming Languages and Compilers and Interpretersen_US
dc.titlePython Machine Learning Case Studiesen_US
dc.title.alternativeFive Case Studies for the Data Scientist /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.dc006 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorHaroon, Danish. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:34Z-
dc.date.available2020-05-17T08:23:34Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484228234 ;en_US
dc.identifier.isbn9781484228227 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/934-
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484228227. ;en_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractEmbrace machine learning approaches and Python to enable automatic rendering of rich insights. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Studyetakes you through the steps to improve business processes and determine the pivotal points that frame strategies. Youeell see machine learning techniques that you can use to support your products and services. Moreover youeell learn the pros and cons of each of the machine learning concepts presented. By taking a step-by-step approach to coding in Python youeell be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure th at you understand the data science approach to solving real-world problems. You will: Gain insights into machine learning conceptse Work on real-world applications of machine learning Get a hands-on overview to Python from a machine learning point of view. ;en_US
dc.description.statementofresponsibilityby Danish Haroon.en_US
dc.description.tableofcontentsChapter 1: eStatistics and Probability -- Chapter 2: eRegression -- Chapter 3: Time series models -- Chapter 4: Classification and Clustering -- Chapter 5: Ensemble methods. ;en_US
dc.format.extentXVII, 204 p. 120 illus., 99 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484228234.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputer Programmingen_US
dc.subjectProgramming Languages and Electronic Computersen_US
dc.subjectDatabase Managementen_US
dc.subjectComputersen_US
dc.subjectComputer Scienceen_US
dc.subjectComputing Methodologies. ;en_US
dc.subjectPython. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectProgramming Languages and Compilers and Interpretersen_US
dc.titlePython Machine Learning Case Studiesen_US
dc.title.alternativeFive Case Studies for the Data Scientist /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.dc006 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484228234.pdf8.14 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHaroon, Danish. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:34Z-
dc.date.available2020-05-17T08:23:34Z-
dc.date.issued2017en_US
dc.identifier.isbn9781484228234 ;en_US
dc.identifier.isbn9781484228227 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/934-
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484228227. ;en_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractEmbrace machine learning approaches and Python to enable automatic rendering of rich insights. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Studyetakes you through the steps to improve business processes and determine the pivotal points that frame strategies. Youeell see machine learning techniques that you can use to support your products and services. Moreover youeell learn the pros and cons of each of the machine learning concepts presented. By taking a step-by-step approach to coding in Python youeell be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure th at you understand the data science approach to solving real-world problems. You will: Gain insights into machine learning conceptse Work on real-world applications of machine learning Get a hands-on overview to Python from a machine learning point of view. ;en_US
dc.description.statementofresponsibilityby Danish Haroon.en_US
dc.description.tableofcontentsChapter 1: eStatistics and Probability -- Chapter 2: eRegression -- Chapter 3: Time series models -- Chapter 4: Classification and Clustering -- Chapter 5: Ensemble methods. ;en_US
dc.format.extentXVII, 204 p. 120 illus., 99 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484228234.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectComputer Programmingen_US
dc.subjectProgramming Languages and Electronic Computersen_US
dc.subjectDatabase Managementen_US
dc.subjectComputersen_US
dc.subjectComputer Scienceen_US
dc.subjectComputing Methodologies. ;en_US
dc.subjectPython. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectProgramming Languages and Compilers and Interpretersen_US
dc.titlePython Machine Learning Case Studiesen_US
dc.title.alternativeFive Case Studies for the Data Scientist /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.dc006 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484228234.pdf8.14 MBAdobe PDFThumbnail
Preview File