東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Google Cloud Platform for data scien...

Sukhdeve, Shitalkumar R.

FindBook

Google Book

Amazon

博客來

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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Google Cloud Platform for data science/ by Dr. Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve.
其他題名:	a crash course on big data, machine learning, and data analytics services /
作者:	Sukhdeve, Shitalkumar R.
其他作者:	Sukhdeve, Sandika S.
出版者:	Berkeley, CA :Apress : : 2023.,
面頁冊數:	xix, 219 p. :illustrations, digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Cloud computing. -
電子資源:	https://doi.org/10.1007/978-1-4842-9688-2
ISBN:	9781484296882

Google Cloud Platform for data science = a 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

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

1016782
Cloud computing.

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

Dewey Class. No.: 004.6782

Google Cloud Platform for data science = a crash course on big data, machine learning, and data analytics services /
LDR:03465nmm a2200325 a 4500 001 2336421
003 DE-He213
005 20231117182159.0
006 m d
007 cr nn 008maaau
008 240402s2023 cau s 0 eng d
020 $a 9781484296882 $q (electronic bk.)
020 $a 9781484296875 $q (paper)
024 7 $a 10.1007/978-1-4842-9688-2 $2 doi
035 $a 978-1-4842-9688-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.585 $b .S85 2023
072 7 $a UTC $2 bicssc
072 7 $a COM000000 $2 bisacsh
072 7 $a UTC $2 thema
082 0 4 $a 004.6782 $2 23
090 $a QA76.585 $b .S948 2023
100 1 $a Sukhdeve, Shitalkumar R. $3 3669493
245 1 0 $a Google Cloud Platform for data science $h [electronic resource] : $b a crash course on big data, machine learning, and data analytics services / $c by Dr. Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2023.
300 $a xix, 219 p. : $b illustrations, digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Cloud computing. $3 1016782
650 1 4 $a Cloud Computing. $3 3231328
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Sukhdeve, Sandika S. $3 3669494
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-9688-2
950 $a Professional and Applied Computing (SpringerNature-12059)