This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
However, putting an ML model into production at scale is challenging and requires a set of bestpractices. Integrations with CI/CD workflows and data versioning promote MLOps bestpractices such as governance and monitoring for iterative development and data versioning. The solution deploys two linked pipelines.
In this post, we illustrate how Accenture uses CodeWhisperer in practice to improve developer productivity. Accenture is using Amazon CodeWhisperer to accelerate coding as part of our software engineering bestpractices initiative in our Velocity platform,” says Balakrishnan Viswanathan, Senior Manager, Tech Architecture at Accenture.
With the advancements in automation and configuring with increasing levels of abstraction to set up different environments with IaC tools, the AWS CDK is being widely adopted across various enterprises. The following diagram illustrates the solution architecture. The unit tests are located in DeepRacer/test/deep_racer.test.ts
Every organization has its own set of standards and practices that provide security and governance for their AWS environment. Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.
Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage infrastructure. Be backed by enterprise grade security and privacy tooling.
We organize all of the trending information in your field so you don't have to. Join 34,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content