Google Cloud Platform for data science : a crash course on big data, machine learning, and data analytics services / Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve.
Sukhdeve, Shitalkumar R. author.; Sukhdeve, Sandika S. author.
2023
QA76.585 .S85 2023
Available Online

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Title Google Cloud Platform for data science : a crash course on big data, machine learning, and data analytics services / Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve.
Author Sukhdeve, Shitalkumar R. author.
ISBN 9781484296882 electronic book
1484296885 electronic book
9781484296875
1484296877
DOI https://doi.org/10.1007/978-1-4842-9688-2
Published Berkeley, CA : Apress, [2023]
Language English
Description 1 online resource (xix, 219 pages) : illustrations
Item Number 10.1007/978-1-4842-9688-2 doi
Call Number QA76.585 .S85 2023
Dewey Decimal Classification 004.6782
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Description based on online resource; title from digital title page (viewed on November 30, 2023).
Added Author Sukhdeve, Sandika S. author.
Available in Other Form Print version: 9781484296875
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Record Appears in Online Resources > Ebooks
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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.

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