Trenton Potgieter

Automated Machine Learning on AWS (eBook, ePUB)

Fast-track the development of your production-ready machine learning applications the AWS way

• Format: ePub

Produktbeschreibung

AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services.
Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team.
By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production.

Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 420
• Erscheinungstermin: 15. April 2022
• Englisch
• ISBN-13: 9781801814522
• Artikelnr.: 70296219

Autorenporträt

Trenton Potgieter is a Sr. AI/ML Specialist at AWS and has been working in the field of machine learning since 2011. At AWS, he assists multiple AWS customers to create ML solutions and has contributed to various use cases broadly spanning computer vision, knowledge graphs, and ML automation using MLOps methodologies. Trenton plays a key role in evangelizing the AWS ML services and shares best practices through forums such as AWS blogs, whitepapers, reference architectures, and public-speaking events. He has also actively been involved in leading, developing, and supporting an AWS internal community of MLOps-related subject matter experts.