Data Science on the Google Cloud Platform: Implementing End-to-End Real-time Data Pipelines: from ingest to machine learningКНИГИ » ПРОГРАММИНГ
Название: Data Science on the Google Cloud Platform: Implementing End-to-End Real-time Data Pipelines: from ingest to machine learning Автор: Valliappa Lakshmanan Издательство: O'Reilly Media Год: 2018 Страниц: 410 Формат: EPUB Размер: 13 Mb Язык: English
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 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 book, you’ll work through a sample business decision by employing a variety of data science approaches.
Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.
You’ll learn how to:
Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out 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 Use your deployed model as a microservice you can access from both batch and real-time pipelines