SKU/Artículo: AMZ-1491974567

Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning

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Paperback

Detalles del producto
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En stock
Peso con empaque:
0.65 kg
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Condición
Nuevo
Producto de:
Amazon
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USA

Sobre este producto
  • 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
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AR$280.546
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AR$112.221

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