Data Science on the Google Cloud Platform

Specifications

Book Description

Using the ePub ebook “Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning“; learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This easy hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline; using statistical and machine learning methods and tools on GCP. Through the course of the ebook; you will work through a sample business decision by employing a variety of data science approaches.

Follow along by implementing these machine learning and statistical solutions in your own project on GCP; and discover how this platform provides a transformative and more collaborative way of doing data science.

You will learn how to:

• • Create a Bayesian model on a Cloud Dataproc cluster

• • Create and populate a dashboard in Google Data Studio

• • Conduct interactive data exploration with Google BigQuery

• • Create a high-performing prediction model with TensorFlow

• • Make a logistic regression machine-learning model with Spark

• • Compute time-aggregate features with a Cloud Dataflow pipeline

• • Build a real-time analysis pipeline to carry out streaming analytics

• • Automate and schedule data ingest; using an App Engine application

• • Use your deployed model as a microservice you can access from both batch and real-time pipelines