OM DENNE EPISODE
It's difficult to find off-the-shelf, open-source solutions for creating lean, simple, and language-agnostic data-processing pipelines for machine learning (ML). This session shows you how to use Amazon S3, Docker, Amazon EC2, Auto Scaling, and a number of open source libraries as cornerstones to build one. We also share our experience creating elastically scalable and robust ML infrastructure leveraging the Spot instance market.
Engelsk
USA
UDSKRIFT 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
SØG BLANDT TIDLIGERE EPISODER
Søg efter gamle afsnit af AWS re:Invent 2015.
ANDRE EPISODE I DENNE PODCAST
You may already know that you can use Amazon CloudWatch to view graphs of your AWS resources like Amazon Elastic Compute Cloud instances or Amazon Simple Storage Service. But, did you know that you can monitor your on-premises servers with Amazon CloudWatch Logs? Or, that you can integrate CloudWat…
Two trends are driving app development: The shift from the server-based web to rich applications that run on a diverse set of mobile devices and modern browsers, and the growth of microservices running in the cloud that serve these clients. The results are "connected clients" - apps with the proces…
An end-to-end, over-the-top (OTT) video system is built of many interdependent architectural tiers, ranging from content preparation, content delivery, and subscriber and entitlement management, to analytics and recommendations. This talk will provide a detailed exploration of how to architect a me…
AWS OpsWorks helps you deploy and operate applications of all shapes and sizes. With AWS OpsWorks, you can model your application stack with layers that define the building blocks of your application: load balancers, application servers, databases, etc. But did you know that you can also use AWS Op…
Ansvarsfraskrivelse: Podcasten og kunstværket, der er indlejret på denne side, er fra Amazon Web Services, som tilhører dens ejer og ikke er tilknyttet eller godkendt af Listen Notes, Inc.
REDIG
Tak fordi du hjælper med at holde podcast-databasen opdateret.
