Deep Dive: Continuous Delivery for AI Applications with ECS

Deep Dive: Continuous Delivery for AI Applications with ECS

Deep learning (DL) is a computer science field derived from the Artificial Intelligence discipline. DL systems are usually developed by data scientists, who are good at mathematics and computer science. But to deploy and operationalize these models for broader use, you need the DevOps mindset and tools. In this tech talk, we’ll show you how to connect the workflow between the data scientists and DevOps.

We’ll explore basic continuous integration and delivery concepts and how they can be applied to deep learning models. Using a number of AWS services, we will showcase how you can take the output of a deep learning model and deploy it to perform predictions in real time with low latency and high availability. In particular, we will showcase the ease of deploying DL predict functions using Apache MXNet (a deep learning library), Amazon ECS, Amazon S3, and Amazon ECR, Amazon developer tools, and AWS CloudFormation

When: May 23 | 12:00 PM - 01:00 PM PT | 03:00 PM - 04:00 PM ET

Learning Objectives:
• Learn how you can use the practices of continuous integration and delivery for operationalizing data science and machine learning applications
• Learn how you can use AWS CodePipeline, AWS CloudFormation and Amazon EC2 Container Service along with MXNet to build and deploy deep learning applications

Who Should Attend: Data Scientists, Developers, Data Engineers

Speakers: Asif Khan, Solutions Architect, AWS

Register for the Webinar