Google Cloud Platform for Data Science: A Crash Course on Big Data, Machine Learning, and Data Analytics Services (Paperback)
暫譯: Google Cloud Platform 數據科學入門：大數據、機器學習與數據分析服務速成課程 (平裝本)

Sukhdeve, Shitalkumar R., Sukhdeve, Sandika S.

Google Cloud Platform for Data Science: A Crash Course on Big Data, Machine Learning, and Data Analytics Services (Paperback)

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商品描述

Data science and machine learning are increasingly becoming critical to businesses of all sizes, and the cloud provides a powerful platform for these applications. Google Cloud Platform (GCP) offers a range of data science services that can be used to store, process, and analyze large datasets, as well as train and deploy machine learning models. This book provides a comprehensive guide to learning GCP for data science, using only the free tier services offered by the platform.

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 that illustrate 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

How to set up a GCP account and project

BigQuery and its use cases, including machine learning

Google Cloud AI Platform and its capabilities

How to use Vertex AI for training and deploying machine

learning models

Google Cloud Dataproc and its use cases for big data processing

How to create and share data visualizations and reports with Looker Data Studio

Google Cloud Dataflow and its use cases for batch and stream data processing

Running data processing pipelines on Cloud Dataflow

Google Cloud Storage and its use cases for data storage

An introduction to Google Cloud SQL and its use cases for relational databases

An introduction to Google Cloud Pub/Sub and its use cases for real-time data streaming

 

Who This Book Is for:

A practical guide designed for data scientists, machine learning engineers, and analysts who want to learn how to use Google Cloud Platform (GCP) for their data science and big data projects.

商品描述(中文翻譯)

資料科學和機器學習正日益成為各種規模企業的關鍵，而雲端提供了這些應用的強大平台。Google Cloud Platform (GCP) 提供了一系列資料科學服務，可用於儲存、處理和分析大型數據集，以及訓練和部署機器學習模型。本書提供了一個全面的指南，幫助讀者學習如何使用 GCP 進行資料科學，僅使用該平台提供的免費層服務。

本書分為七個章節，涵蓋各種主題，如 GCP 帳戶設置、Google Colaboratory、大數據與機器學習、資料視覺化與商業智慧、資料處理與轉換、資料分析與儲存，以及進階主題。每個章節提供逐步的指導和示例，說明如何在資料科學和大數據專案中使用 GCP 服務。

讀者將學習如何設置 Google Colaboratory 帳戶並運行 Jupyter notebooks，訪問 GCP 服務和 Colaboratory 中的數據，使用 BigQuery 進行資料分析，以及使用 Vertex AI 部署機器學習模型。本書還涵蓋如何使用 Looker Data Studio 進行資料視覺化，使用 Google Cloud Dataflow 和 Dataprep 運行資料處理管道，以及使用 Google Cloud Storage 和 SQL 儲存數據。

您將學到的內容

如何設置 GCP 帳戶和專案

BigQuery 及其使用案例，包括機器學習

Google Cloud AI Platform 及其功能

如何使用 Vertex AI 進行機器學習模型的訓練和部署

Google Cloud Dataproc 及其在大數據處理中的使用案例

如何使用 Looker Data Studio 創建和分享資料視覺化和報告

Google Cloud Dataflow 及其在批次和串流資料處理中的使用案例

在 Cloud Dataflow 上運行資料處理管道

Google Cloud Storage 及其在資料儲存中的使用案例

Google Cloud SQL 及其在關聯資料庫中的使用案例介紹

Google Cloud Pub/Sub 及其在實時資料串流中的使用案例介紹

本書適合誰閱讀：

本書是為資料科學家、機器學習工程師和分析師設計的實用指南，旨在幫助他們學習如何使用 Google Cloud Platform (GCP) 進行資料科學和大數據專案。

作者簡介

Shitalkumar R. Sukhdeve is an experienced senior data scientist with a strong track record of developing and deploying transformative data science and machine learning solutions to solve complex business problems in the telecom industry. He has notable achievements in developing a machine learning-driven customer churn prediction and root cause exploration solution, a customer credit scoring system, and a product recommendation engine.

Shitalkumar is skilled in enterprise data science and research ecosystem development, dedicated to optimizing key business indicators, and adding revenue streams for companies. He is pursuing a doctorate in business administration from SSBM, Switzerland, and an M.Tech in computer science and engineering from VNIT Nagpur.

Shitalkumar has authored a book titled Step Up for Leadership in Enterprise Data Science and Artificial Intelligence with Big Data: Illustrations with R and Python and co-authored a book titled Web Application Development with R Using Shiny, 3rd edition. He is a speaker at various technology and business events such as WorldAI Show Jakarta 2021, 2022, and 2023, NXT CX Jakarta 2022, Global Cloud Native Open Source Summit 2022, Cyber Security Summit 2022, and ASEAN Conversational Automation Webinar. You can find him on LinkedIn.

Sandika S. Sukhdeve is an expert in Data Visualization and Google-certified Project Management. She previously served as Assistant Professor in a Mechanical Engineering Department and has authored Amazon bestseller titles across diverse markets such as the USA, Germany, Canada, and more. She has a background in Human Resources and a wealth of experience in Branding.

As an Assistant Professor, she successfully guided more than 2,000 students and delivered 1,000+ lectures, and mentored numerous projects (including Computational Fluid Dynamics). She excels in managing both people and multiple projects, ensuring timely completion. Her areas of specialization encompass Thermodynamics, Applied Thermodynamics, Industrial Engineering, Product Design and Development, Theory of Machine, Numerical Methods and Optimization, and Fluid Mechanics. She holds a master's degree in Technology (with a Specialization in Heat-Power), and she possesses exceptional skills in visualizing, analyzing, and constructing classification and prediction models using R and MATLAB. You can find her on LinkedIn.

作者簡介(中文翻譯)

**Shitalkumar R. Sukhdeve** 是一位經驗豐富的資深數據科學家，擁有在電信行業開發和部署變革性數據科學及機器學習解決方案以解決複雜商業問題的良好紀錄。他在開發基於機器學習的客戶流失預測及根本原因探索解決方案、客戶信用評分系統和產品推薦引擎方面有顯著成就。

Shitalkumar 精通企業數據科學和研究生態系統的發展，致力於優化關鍵商業指標並為公司增加收入來源。他目前正在瑞士SSBM攻讀商業管理博士學位，並在VNIT Nagpur獲得計算機科學與工程的碩士學位。

Shitalkumar 著有一本書，名為 *Step Up for Leadership in Enterprise Data Science and Artificial Intelligence with Big Data: Illustrations with R and Python*，並共同撰寫了 *Web Application Development with R Using Shiny, 3rd edition*。他是多個技術和商業活動的演講者，如2021、2022和2023年的WorldAI Show Jakarta、2022年的NXT CX Jakarta、2022年的Global Cloud Native Open Source Summit、2022年的Cyber Security Summit，以及ASEAN Conversational Automation Webinar。您可以在LinkedIn上找到他。

**Sandika S. Sukhdeve** 是數據可視化和Google認證的項目管理專家。她曾擔任機械工程系的助理教授，並在美國、德國、加拿大等多個市場著有亞馬遜暢銷書。她擁有人力資源背景，並在品牌塑造方面擁有豐富的經驗。

作為助理教授，她成功指導了超過2,000名學生，並進行了1,000多場講座，還指導了多個項目（包括計算流體力學）。她擅長管理人員和多個項目，確保按時完成。她的專業領域包括熱力學、應用熱力學、工業工程、產品設計與開發、機械理論、數值方法與優化以及流體力學。她擁有技術碩士學位（專攻熱能），並在使用R和MATLAB進行可視化、分析及構建分類和預測模型方面具備卓越技能。您可以在LinkedIn上找到她。

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