Isbn: 9781098118952 - data science on the google cloud platform: implementing end-to-end real-time data pipelines: from ingest to machine learning (14 Ergebnisse)

Paperback. Zustand: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Paperback. Zustand: Very Good. Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.…

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

Zustand: New. 2022. 2nd ed. Paperback. . . . . . Books ship from the US and Ireland.

Zustand: New.

Paperback. Zustand: Brand New. 2nd edition. 450 pages. 9.19x7.00x0.93 inches. In Stock.

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Taschenbuch. Zustand: Neu. Neuware - Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: - Employ best practices in building highly scalable data and ML pipelines on Google Cloud - Automate and schedule data ingest using Cloud Run - Create and populate a dashboard in Data Studio - Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery - Conduct interactive data exploration with BigQuery - Create a Bayesian model with Spark on Cloud Dataproc - Forecast time series and do anomaly detection with BigQuery ML - Aggregate within time windows with Dataflow - Train explainable machine learning models with Vertex AI - Operationalize ML with Vertex AI Pipelines.…

Zustand: New. &Uumlber den AutorValliappa (Lak) Lakshmanan is the director of analytics and AI solutions at Google Cloud, where he leads a team building cross-industry solutions to business problems. His mission is to democratize machine learning .

Zustand: Gut. Zustand: Gut | Seiten: 459 | Sprache: Englisch | Produktart: Bücher | Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: - Employ best practices in building highly scalable data and ML pipelines on Google Cloud - Automate and schedule data ingest using Cloud Run - Create and populate a dashboard in Data Studio - Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery - Conduct interactive data exploration with BigQuery - Create a Bayesian model with Spark on Cloud Dataproc - Forecast time series and do anomaly detection with BigQuery ML - Aggregate within time windows with Dataflow - Train explainable machine learning models with Vertex AI - Operationalize ML with Vertex AI Pipelines.…

Taschenbuch. Zustand: Neu. Data Science on the Google Cloud Platform | Implementing End-To-End Real-Time Data Pipelines: From Ingest to Machine Learning | Valliappa Lakshmanan | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | O'Reilly Media | EAN 9781098118952 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…