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

Description

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, youll 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.

Youll 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

Author: Valliappa Lakshmanan
Binding Type: Paperback
Publisher: OReilly Media
Published: 05/03/2022
Pages: 459
Weight: 1.61lbs
Size: 9.19h x 7.00w x 0.93d
ISBN: 9781098118952
Language: English