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Titlebook: Google Cloud Platform for Data Science; A Crash Course on Bi Dr. Shitalkumar R. Sukhdeve,Sandika S. Sukhdeve Book 2023 Shitalkumar R. Sukhd

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發(fā)表于 2025-3-21 18:04:16 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Google Cloud Platform for Data Science
副標(biāo)題A Crash Course on Bi
編輯Dr. Shitalkumar R. Sukhdeve,Sandika S. Sukhdeve
視頻videohttp://file.papertrans.cn/388/387394/387394.mp4
概述Teaches GCP data science services—step by step—using the free tier offerings.Reviews advanced topics such as Dataplex, Cloud Data Fusion, and Looker Data Studio.Takes a deep dive into Google Colaborat
圖書(shū)封面Titlebook: Google Cloud Platform for Data Science; A Crash Course on Bi Dr. Shitalkumar R. Sukhdeve,Sandika S. Sukhdeve Book 2023 Shitalkumar R. Sukhd
描述.This book is your practical and comprehensive guide to learning Google Cloud Platform (GCP) for data science, using only the free tier services offered by the platform..Data science and machine learning are increasingly becoming critical to businesses of all sizes, and the cloud provides a powerful platform for these applications. GCP offers a range of data science services that can be used to store, process, and analyze large datasets, and train and deploy machine learning models..The book is organized into seven chapters covering various topics such as GCP account setup, Google Colaboratory, Big Data and Machine Learning, Data Visualization and Business Intelligence, Data Processing and Transformation, Data Analytics and Storage, and Advanced Topics. Each chapter provides step-by-step instructions and examples illustrating how to use GCP services for data science and big data projects..Readers will learn how to set up a Google Colaboratory account and run Jupyternotebooks, access GCP services and data from Colaboratory, use BigQuery for data analytics, and deploy machine learning models using Vertex AI. The book also covers how to visualize data using Looker Data Studio, run dat
出版日期Book 2023
關(guān)鍵詞Google Cloud Platform; GCP; Data Science; Big Data; Jupyter Notebooks; Data Analytics; Google Colaboratory
版次1
doihttps://doi.org/10.1007/978-1-4842-9688-2
isbn_softcover978-1-4842-9687-5
isbn_ebook978-1-4842-9688-2
copyrightShitalkumar R. Sukhdeve and Sandika S. Sukhdeve 2023
The information of publication is updating

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https://doi.org/10.1007/978-94-009-0315-9This chapter delves into advanced aspects of securing and managing Google Cloud Platform (GCP) resources, version control using Google Cloud Source Repositories, and powerful data integration tools: Dataplex and Cloud Data Fusion.
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Data Analytics and Storage,This chapter delves into data analytics and storage, spotlighting Google Cloud Storage, Google Cloud SQL, and Google Cloud Pub/Sub. We commence with Google Cloud Storage, a scalable object storage solution. It finds utility in data archiving, hosting websites, and backups. We explore its features and compatibility with other Google services.
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發(fā)表于 2025-3-22 11:25:01 | 只看該作者
Advanced Topics,This chapter delves into advanced aspects of securing and managing Google Cloud Platform (GCP) resources, version control using Google Cloud Source Repositories, and powerful data integration tools: Dataplex and Cloud Data Fusion.
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https://doi.org/10.1007/978-1-4842-9688-2Google Cloud Platform; GCP; Data Science; Big Data; Jupyter Notebooks; Data Analytics; Google Colaboratory
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發(fā)表于 2025-3-22 22:31:28 | 只看該作者
Introduction to GCP,ogle’s products. In this chapter, we introduced GCP, highlighting its core services and their significance within the context of data science. We delved into a number of vital GCP services for data science, such as BigQuery, Cloud AI Platform, Cloud Dataflow, Cloud DataLab, Cloud Dataproc, Cloud Sto
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