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

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.

數據科學和機器學習對於各種規模的企業來說越來越重要，而雲端為這些應用提供了強大的平台。Google Cloud Platform（GCP）提供了一系列的數據科學服務，可用於存儲、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，教你如何使用GCP進行數據科學，並僅使用平台提供的免費服務。

本書分為七章，涵蓋了各種主題，如GCP帳戶設置、Google Colaboratory、大數據和機器學習、數據可視化和商業智能、數據處理和轉換、數據分析和存儲，以及高級主題。每一章都提供了逐步指導和示例，演示如何使用GCP服務進行數據科學和大數據項目。

讀者將學習如何設置Google Colaboratory帳戶並運行Jupyter筆記本，訪問GCP服務和Colaboratory中的數據，使用BigQuery進行數據分析，並使用Vertex AI部署機器學習模型。本書還介紹了如何使用Looker Data Studio對數據進行可視化，使用Google Cloud Dataflow和Dataprep運行數據處理流程，以及使用Google Cloud Storage和SQL存儲數據。

你將學到什麼
- 如何設置GCP帳戶和項目
- BigQuery及其應用案例，包括機器學習
- Google Cloud AI平台及其功能
- 如何使用Vertex AI進行機器學習模型的訓練和部署
- Google Cloud Dataproc及其用於大數據處理的應用案例
- 如何使用Looker Data Studio創建和共享數據可視化和報告
- Google Cloud Dataflow及其用於批處理和流處理數據的應用案例
- 在Cloud Dataflow上運行數據處理流程
- Google Cloud Storage及其用於數據存儲的應用案例
- Google Cloud SQL的介紹及其用於關聯數據庫的應用案例
- Google Cloud Pub/Sub的介紹及其用於實時數據流的應用案例

本書適合對象：
本書是一本實用指南，適用於希望學習如何在其數據科學和大數據項目中使用Google Cloud Platform（GCP）的數據科學家、機器學習工程師和分析師。

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.

Shitalkumar R. Sukhdeve是一位經驗豐富的高級數據科學家，擁有在電信行業解決複雜業務問題的轉型數據科學和機器學習解決方案的強大紀錄。他在開發基於機器學習的客戶流失預測和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取得了顯著成就。

Shitalkumar擅長企業數據科學和研究生態系統的發展，致力於優化關鍵業務指標，為公司增加收入流。他正在瑞士SSBM攻讀工商管理博士學位，並在VNIT Nagpur攻讀計算機科學和工程學的碩士學位。

Shitalkumar撰寫了一本名為《使用R和Python進行企業數據科學和人工智能大數據的領導力提升》的書籍，並共同撰寫了一本名為《使用Shiny進行R的Web應用程序開發，第三版》的書籍。他是各種技術和商業活動的演講嘉賓，例如2021年、2022年和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和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。她曾在機械工程系擔任助理教授，並在美國、德國、加拿大等不同市場上撰寫了亞馬遜暢銷書籍。她在人力資源方面有背景，並在品牌推廣方面擁有豐富的經驗。

作為助理教授，她成功指導了2000多名學生，進行了1000多場講座，並指導了眾多項目（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、產品設計和開發、機械理論、數值方法和優化以及流體力學。她擁有技術碩士學位（專攻熱能動力學），並具有使用R和MATLAB進行可視化、分析和構建分類和預測模型的卓越技能。您可以在LinkedIn上找到她。