AWS CodeCommit VS Amazon Rekognition

AWS CodeCommit Reviews

Amazon Rekognition Reviews

AWS CodeCommit mentions (22)

• DevSecOps with AWS- IaC at scale - Building your own platform - Part 1

  AWS CodeCommit: secure, highly scalable, managed source control service that hosts private Git repositories. - Source: dev.to / about 2 months ago

• Passing the AWS Certified DevOps Engineer - Professional exam

  AWS CodeCommit is AWS's hosted GitHub in the cloud. It is integrated with IAM and you should understand how different levels of permissions that can be granted to users of the service. Know what the AWSCodeCommitPowerUser policy is for. You can receive notifications via SNS to invoke downstream actions in AWS CodeBuild, AWS CodePipeline or other competing services. - Source: dev.to / 3 months ago

• A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev

  CodeCommit - 5 active users,50GB storage, and 10000 requests per month. - Source: dev.to / 3 months ago

• Setting up my own landing zone on AWS

  Build – Used for all CodeCommit repositories and CodePipelines that are deployed within the landing zone. - Source: dev.to / 5 months ago

• Unveiling CodiumAI PR-Agent: A Comparative Analysis Against GitHub Copilot for Pull Requests

  PR-Agent offers extensive pull request functionalities across various git providers: GitHub, GitLab, or Bitbucket, CodeCommit, Azure DevOps, Gerrit. - Source: dev.to / 5 months ago

Amazon Rekognition mentions (33)

• Afraid of outgrowing AWS Rekognition? Try YOLO in Lambda.

  AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 2 months ago

• Amazon Rekognition Custom Labels for Bears

  I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 10 months ago

• “During a gold rush, sell shovels.” What are the shovels in the AI rush?

  For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago

• Serverless Facial Recognition Voting Application Using AWS Services

  Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / about 1 year ago

• Amazon Prime Video playback features

  Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago