Data Science on the Google Cloud Platform: By Valliappa Lakshmanan

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Data Science on the Google Cloud Platform: By Valliappa Lakshmanan: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning. When you create using Google Cloud Platform, you’ll see how simple it is to apply complex statistical and machine learning algorithms to real-world situations (GCP).

Sumamry Data Science on the Google Cloud Platform

This hands-on guide demonstrates data engineers and data scientists how to use statistical and machine learning methods and tools on GCP to build an end-to-end data pipeline.

Throughout this enhanced second edition, you’ll work through a typical business decision using a range of data science methodologies. Implement these statistics and machine learning solutions in your project on GCP to see how this platform can help you undertake data science in a more transformative and collaborative way.

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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

Release Date Data Science on the Google Cloud Platform Pdf

Book Name:Google Cloud for Data Science
Publisher:O’Reilly Media; 2nd edition?
Publishing Date(April 26, 2022)
Language :English
File Size: / Pages446

About Author: Data Science Google Cloud

Valliappa (Lak) Lakshmanan is Google Cloud’s director of analytics and AI solutions, where he oversees a team that develops cross-industry solutions to business problems. His goal is to democratize machine learning so that anyone, anywhere, can perform it.

?Practical Machine Learning for Computer Vision, Machine Learning Design Patterns, Data Governance The Definitive Guide, Google BigQuery The Definitive Guide, and Data Science on the Google Cloud Platform are all written by Lak or co-written by him.

Conclusion: Data Science on the Google Cloud Platform 2nd Edition Review

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