Data Science on the Google Cloud Platform : Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning
Uloženo v:
| Název: | Data Science on the Google Cloud Platform : Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning |
|---|---|
| Popis: | Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches.Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.You'll learn how to:Automate and schedule data ingest, using an App Engine applicationCreate and populate a dashboard in Google Data StudioBuild a real-time analysis pipeline to carry out streaming analyticsConduct interactive data exploration with Google BigQueryCreate a Bayesian model on a Cloud Dataproc clusterBuild a logistic regression machine-learning model with SparkCompute time-aggregate features with a Cloud Dataflow pipelineCreate a high-performing prediction model with TensorFlowUse your deployed model as a microservice you can access from both batch and real-time pipelines |
| Autoři: | Valliappa Lakshmanan |
| Resource Type: | eBook. |
| Témata: | Cloud computing, Real-time data processing, Computing platforms |
| Categories: | COMPUTERS / Data Science / General, COMPUTERS / Database Administration & Management, COMPUTERS / Data Science / Data Modeling & Design |
| Databáze: | eBook Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: edsebk DbLabel: eBook Index An: 1655721 RelevancyScore: 937 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 937.174743652344 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Data Science on the Google Cloud Platform : Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning – Name: Abstract Label: Description Group: Ab Data: Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches.Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.You'll learn how to:Automate and schedule data ingest, using an App Engine applicationCreate and populate a dashboard in Google Data StudioBuild a real-time analysis pipeline to carry out streaming analyticsConduct interactive data exploration with Google BigQueryCreate a Bayesian model on a Cloud Dataproc clusterBuild a logistic regression machine-learning model with SparkCompute time-aggregate features with a Cloud Dataflow pipelineCreate a high-performing prediction model with TensorFlowUse your deployed model as a microservice you can access from both batch and real-time pipelines – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Valliappa+Lakshmanan%22">Valliappa Lakshmanan</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+data+processing%22">Real-time data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Computing+platforms%22">Computing platforms</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+General%22">COMPUTERS / Data Science / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Database+Administration+%26+Management%22">COMPUTERS / Database Administration & Management</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Data+Modeling+%26+Design%22">COMPUTERS / Data Science / Data Modeling & Design</searchLink> |
| PLink | https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1655721 |
| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 004.33 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Cloud computing Type: general – SubjectFull: Real-time data processing Type: general – SubjectFull: Computing platforms Type: general Titles: – TitleFull: Data Science on the Google Cloud Platform : Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Valliappa Lakshmanan – PersonEntity: Name: NameFull: Valliappa Lakshmanan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2018 – D: 22 M: 12 Type: profile Y: 2017 Identifiers: – Type: isbn-print Value: 9781491974568 – Type: isbn-electronic Value: 9781491974537 Titles: – TitleFull: Data Science on the Google Cloud Platform : Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning Type: main |
| ResultId | 1 |