Data Science on the Google Cloud Platform

Developers can easily apply sophisticated statistical and machine learning methods to real-world problems with the Google Cloud Platform (GCP). This hands-on guide demonstrates how to implement an end-to-end data pipeline using statistical and machine learning tools and techniques on GCP. By following along with examples and implementing solutions in their own projects, developers will learn how to automate data ingestion, create dashboards, perform streaming analytics, build Bayesian models, create logistic regression models, compute time-aggregate features, and deploy high-performing prediction models as microservices.

Format: Paperback / softback
Length: 400 pages
Publication date: 05 January 2018
Publisher: O'Reilly Media, Inc, USA

Discover the power of advanced statistical and machine learning techniques by leveraging the Google Cloud Platform (GCP). This comprehensive hands-on guide is designed for developers entering the field of data science, guiding them through the process of implementing an end-to-end data pipeline using statistical and machine learning methods and tools on GCP.

Throughout the course of the book, you will embark on a sample business decision, employing a diverse range of data science approaches. Follow along as you implement these statistical and machine learning solutions in your own project on GCP, experiencing firsthand how this platform empowers data scientists with a transformative and collaborative approach to data science.

In this comprehensive guide, you will learn how to:

Automate and schedule data ingestion using an App Engine application.

Create and populate a dashboard in Google Data Studio.

Build a real-time analysis pipeline for streaming analytics.

Conduct interactive data exploration with Google BigQuery.

Create a Bayesian model on a Cloud Dataproc cluster.

Build a logistic regression machine-learning model with Spark.

Compute time-aggregate features with a Cloud Dataflow pipeline.

Create a high-performing prediction model with TensorFlow.

Deploy your model as a microservice accessible from both batch and real-time pipelines.

By leveraging the capabilities of GCP, you will unlock the full potential of statistical and machine learning techniques, enabling you to solve complex real-world problems with efficiency and precision. Whether you are a seasoned data scientist or just starting your journey, this guide will provide you with the skills and knowledge needed to thrive in the field of data science. So, why wait? Start building your data science projects on GCP today and unlock a world of endless possibilities!

Weight: 706g
Dimension: 180 x 234 x 20 (mm)
ISBN-13: 9781491974568