Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Erscheinungsort nicht ermittelbar]
O'Reilly Media, Inc.
2017
|
| Ausgabe: | 1st edition |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781098192150/?ar |
| Zusammenfassung: | 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 application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines |
| Umfang: | 1 online resource (408 pages) |
| ISBN: | 9781491974551 1491974559 9781491974537 1491974532 |
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| physical | 1 online resource (408 pages) |
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| spelling | Lakshmanan, Valliappa VerfasserIn aut Data Science on the Google Cloud Platform Lakshmanan, Valliappa 1st edition [Erscheinungsort nicht ermittelbar] O'Reilly Media, Inc. 2017 1 online resource (408 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines Google Apps 1491974567 Erscheint auch als Druck-Ausgabe 1491974567 |
| spellingShingle | Lakshmanan, Valliappa Data Science on the Google Cloud Platform Google Apps |
| title | Data Science on the Google Cloud Platform |
| title_auth | Data Science on the Google Cloud Platform |
| title_exact_search | Data Science on the Google Cloud Platform |
| title_full | Data Science on the Google Cloud Platform Lakshmanan, Valliappa |
| title_fullStr | Data Science on the Google Cloud Platform Lakshmanan, Valliappa |
| title_full_unstemmed | Data Science on the Google Cloud Platform Lakshmanan, Valliappa |
| title_short | Data Science on the Google Cloud Platform |
| title_sort | data science on the google cloud platform |
| topic | Google Apps |
| topic_facet | Google Apps |
| work_keys_str_mv | AT lakshmananvalliappa datascienceonthegooglecloudplatform |