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

This book provides a practical and comprehensive guide to learning Google Cloud Platform (GCP) for data science, using only the free tier services offered by the platform. It covers topics such as 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. Readers will learn how to set up a GCP account and project, explore BigQuery and its use cases, 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, explore Google Cloud Storage and its use cases for data storage, and get an introduction to Google Cloud SQL and its use cases for relational databases.

Format: Paperback / softback
Length: 219 pages
Publication date: 19 November 2023
Publisher: APress

This comprehensive guide is designed to help you master Google Cloud Platform (GCP) for data science, utilizing exclusively the free tier services offered by the platform. As data science and machine learning continue to gain immense importance in today's business landscape, the cloud emerges as a powerful platform for these applications. GCP offers a wide array of data science services that empower organizations to efficiently store, process, and analyze large datasets, as well as train and deploy machine learning models.

The book is structured into seven chapters, each covering a diverse range of topics. These chapters include:

GCP Account Setup: This chapter provides step-by-step instructions on how to set up a GCP account and project. It covers topics such as creating a new project, assigning permissions, and configuring billing settings.

Google Colaboratory: Google Colaboratory is a web-based notebook environment that allows you to run Jupyter notebooks and access GCP services and data from within your browser. This chapter covers how to set up a Google Colaboratory account, run Jupyternotebooks, and access GCP services and data.

Big Data and Machine Learning: This chapter explores the concepts of big data and machine learning, and how GCP can be used to handle and analyze large datasets. It covers topics such as data storage, processing, and analysis using BigQuery, Google Cloud Storage, and Google Cloud Dataflow.

Data Visualization and Business Intelligence: This chapter focuses on data visualization and business intelligence using tools such as Looker Data Studio and Google Data Studio. It covers how to create and share data visualizations and reports, as well as how to integrate data with business applications.

Data Processing and Transformation: This chapter covers data processing and transformation using tools such as Google Cloud Dataflow and Dataprep. It covers topics such as data cleaning, transformation, and integration with other GCP services.

Data Analytics and Storage: This chapter explores data analytics and storage using tools such as BigQuery and Google Cloud Storage. It covers topics such as data querying, data mining, and machine learning model training and deployment using BigQuery and Vertex AI.

Advanced Topics: This chapter covers advanced topics in data science and machine learning, such as distributed computing, deep learning, and reinforcement learning. It provides an in-depth understanding of GCP's capabilities in these areas.

Throughout each chapter, the author provides clear and concise instructions, accompanied by step-by-step examples and screenshots. These examples help readers understand how to use GCP services for data science and big data projects, and how to apply them to real-world scenarios.

Whether you are a data scientist, data engineer, or business analyst, this book will provide you with the knowledge and skills needed to leverage GCP for data science and big data projects. By utilizing the free tier services offered by GCP, you can explore the platform's capabilities and develop your skills without incurring any significant costs.

So, if you are ready to take your data science and machine learning skills to the next level, this book is the perfect guide for you. Don't wait any longer; start your journey to mastering GCP today!

Dimension: 235 x 155 (mm)
ISBN-13: 9781484296875
Edition number: 1st ed.