If you use data to make critical business decisions this book is for you. Whether you're a
data analyst research scientist data engineer ML engineer data scientist application
developer or systems developer this guide helps you broaden your understanding of the modern
data science stack create your own machine learning pipelines and deploy them to applications
at production scale. The AWS data science stack unifies data science data engineering and
application development to help you level up your skills beyond your current role. Authors
Antje Barth and Chris Fregly show you how to build your own ML pipelines from existing APIs
submit them to the cloud and integrate results into your application in minutes instead of
days. Innovate quickly and save money with AWS's on-demand serverless and cloud-managed
services Implement open source technologies such as Kubeflow Kubernetes TensorFlow and
Apache Spark on AWS Build and deploy an end-to-end continuous ML pipeline with the AWS data
science stack Perform advanced analytics on at-rest and streaming data with AWS and Spark
Integrate streaming data into your ML pipeline for continuous delivery of ML models using AWS
and Apache Kafka
