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Google Cloud Platform for data sciencea crash course on big data, machine learning, and data analytics services /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Google Cloud Platform for data scienceby Dr. Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve.
Reminder of title:	a crash course on big data, machine learning, and data analytics services /
Author:	Sukhdeve, Shitalkumar R.
other author:	Sukhdeve, Sandika S.
Published:	Berkeley, CA :Apress :2023.
Description:	xix, 219 p. :illustrations, digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Cloud computing.
Online resource:	https://doi.org/10.1007/978-1-4842-9688-2
ISBN:	9781484296882$q(electronic bk.)

Google Cloud Platform for data sciencea crash course on big data, machine learning, and data analytics services /
Sukhdeve, Shitalkumar R.

Google Cloud Platform for data sciencea crash course on big data, machine learning, and data analytics services /[electronic resource] :by Dr. Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve. - Berkeley, CA :Apress :2023. - xix, 219 p. :illustrations, digital ;24 cm.

Chapter 1: Introduction to GCP -- Chapter 2: Google Colaboratory -- Chapter 3: Big Data and Machine Learning -- Chapter 4: Data Visualization and Business Intelligence -- Chapter 5: Data Processing and Transformation -- Chapter 6: Data Analytics and Storage -- Chapter 7: Advanced Topics.

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 Jupyter notebooks, 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 data processing pipelines using Google Cloud Dataflow and Dataprep, and store data using Google Cloud Storage and SQL. What You Will Learn Set up a GCP account and project Explore BigQuery and its use cases, including machine learning Understand Google Cloud AI Platform and its capabilities Use Vertex AI for training and deploying machine learning models Explore Google Cloud Dataproc and its use cases for big data processing Create and share data visualizations and reports with Looker Data Studio Explore Google Cloud Dataflow and its use cases for batch and stream data processing Run data processing pipelines on Cloud Dataflow Explore Google Cloud Storage and its use cases for data storage Get an introduction to Google Cloud SQL and its use cases for relational databases Get an introduction to Google Cloud Pub/Sub and its use cases for real-time data streaming.

ISBN: 9781484296882$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-9688-2doiSubjects--Topical Terms:

378527
Cloud computing.

LC Class. No.: QA76.585 / .S85 2023

Dewey Class. No.: 004.6782

Google Cloud Platform for data sciencea crash course on big data, machine learning, and data analytics services /
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