Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/934
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Haroon, Danish. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:23:34Z | - |
dc.date.available | 2020-05-17T08:23:34Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.isbn | 9781484228234 ; | en_US |
dc.identifier.isbn | 9781484228227 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/934 | - |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | Printed edition: ; 9781484228227. ; | en_US |
dc.description | QA75.5-76.95 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description.abstract | Embrace 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.statementofresponsibility | by Danish Haroon. | en_US |
dc.description.tableofcontents | Chapter 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.extent | XVII, 204 p. 120 illus., 99 illus. in color. ; online resource. ; | en_US |
dc.publisher | Apress : | en_US |
dc.publisher | Imprint: Apress, | en_US |
dc.relation.haspart | 9781484228234.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computer Programming | en_US |
dc.subject | Programming Languages and Electronic Computers | en_US |
dc.subject | Database Management | en_US |
dc.subject | Computers | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computing Methodologies. ; | en_US |
dc.subject | Python. ; | en_US |
dc.subject | Big Data. ; | en_US |
dc.subject | Programming Languages and Compilers and Interpreters | en_US |
dc.title | Python Machine Learning Case Studies | en_US |
dc.title.alternative | Five Case Studies for the Data Scientist / | en_US |
dc.type | Book | en_US |
dc.publisher.place | Berkeley, CA : | en_US |
dc.classification.dc | 006 ; 23 ; | en_US |
Appears in Collections: | مهندسی فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9781484228234.pdf | 8.14 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Haroon, Danish. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:23:34Z | - |
dc.date.available | 2020-05-17T08:23:34Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.isbn | 9781484228234 ; | en_US |
dc.identifier.isbn | 9781484228227 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/934 | - |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | Printed edition: ; 9781484228227. ; | en_US |
dc.description | QA75.5-76.95 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description.abstract | Embrace 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.statementofresponsibility | by Danish Haroon. | en_US |
dc.description.tableofcontents | Chapter 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.extent | XVII, 204 p. 120 illus., 99 illus. in color. ; online resource. ; | en_US |
dc.publisher | Apress : | en_US |
dc.publisher | Imprint: Apress, | en_US |
dc.relation.haspart | 9781484228234.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computer Programming | en_US |
dc.subject | Programming Languages and Electronic Computers | en_US |
dc.subject | Database Management | en_US |
dc.subject | Computers | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computing Methodologies. ; | en_US |
dc.subject | Python. ; | en_US |
dc.subject | Big Data. ; | en_US |
dc.subject | Programming Languages and Compilers and Interpreters | en_US |
dc.title | Python Machine Learning Case Studies | en_US |
dc.title.alternative | Five Case Studies for the Data Scientist / | en_US |
dc.type | Book | en_US |
dc.publisher.place | Berkeley, CA : | en_US |
dc.classification.dc | 006 ; 23 ; | en_US |
Appears in Collections: | مهندسی فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9781484228234.pdf | 8.14 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Haroon, Danish. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:23:34Z | - |
dc.date.available | 2020-05-17T08:23:34Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.isbn | 9781484228234 ; | en_US |
dc.identifier.isbn | 9781484228227 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/934 | - |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | Printed edition: ; 9781484228227. ; | en_US |
dc.description | QA75.5-76.95 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description.abstract | Embrace 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.statementofresponsibility | by Danish Haroon. | en_US |
dc.description.tableofcontents | Chapter 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.extent | XVII, 204 p. 120 illus., 99 illus. in color. ; online resource. ; | en_US |
dc.publisher | Apress : | en_US |
dc.publisher | Imprint: Apress, | en_US |
dc.relation.haspart | 9781484228234.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computer Programming | en_US |
dc.subject | Programming Languages and Electronic Computers | en_US |
dc.subject | Database Management | en_US |
dc.subject | Computers | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computing Methodologies. ; | en_US |
dc.subject | Python. ; | en_US |
dc.subject | Big Data. ; | en_US |
dc.subject | Programming Languages and Compilers and Interpreters | en_US |
dc.title | Python Machine Learning Case Studies | en_US |
dc.title.alternative | Five Case Studies for the Data Scientist / | en_US |
dc.type | Book | en_US |
dc.publisher.place | Berkeley, CA : | en_US |
dc.classification.dc | 006 ; 23 ; | en_US |
Appears in Collections: | مهندسی فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9781484228234.pdf | 8.14 MB | Adobe PDF | Preview File |