Broadcast Date: April 14, 2023
Level: 400
This talk will discuss the benefits of using Rust for MLOps in the Amazon Sagemaker ecosystem. Rust's performance and safety features make it ideal for handling the high-performance computing demands of machine learning. The talk will explore various tools and frameworks in the Amazon Sagemaker ecosystem helpful with Rust to build efficient and scalable MLOps pipelines, such as the combination of AWS Lambda, ONNX, and PyTorch. Through real-world examples, the talk will demonstrate how Rust can help teams optimize their machine-learning workflows in Amazon Sagemaker. Whether you are a seasoned developer or just starting in MLOps, this talk will provide valuable insights.
Learning Objectives
- Educate attendees on the benefits of using Rust for MLOps in the AWS Sagemaker ecosystem, including leveraging Rust's performance and safety features to handle high-performance computing demands of machine learning.
- Introduce the tools and frameworks available in the AWS Sagemaker ecosystem that are useful with Rust to build efficient and scalable MLOps pipelines, such as the combination of AWS Lambda, ONNX, Cloud9, and PyTorch.
- Provide real-world examples to demonstrate how Rust can help teams optimize their machine learning workflows in AWS Sagemaker, regardless of their level of expertise in MLOps.
Who Should Attend?
ML Engineers, ML Developers, Data Scientists
Speaker(s)
Noah Gift, Founder, Pragmatic A.I. Labs, AWS ML Hero, Duke Executive in Residence
Learn More
To learn more about the services featured in this talk, please visit:
aws.amazon.com/sagemaker/mlops/?sagemaker-data-wrangler-whats-new
Intro body copy here about 2018 re:Invent launches.
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