In this final part, we will focus on leveraging cloud infrastructure with CML; enabling automatic reporting (graphs, images, reports and tables with performance metrics) for PRs; and the eventual deployment process.
In most cases, training a well-performing Computer Vision (CV) model is not the hardest part of building a Computer Vision-based system. The hardest parts are usually about incorporating this model into a maintainable application that runs in a production environment bringing value to the customers and our business.
In this guide we will show how you can use CML to automatically retrain a model and save its outputs to your Github repository using a provisioned AWS EC2 runner.
Monthly updates are here! You will find the future of AI Infrastruture is modular, articles on distribution drift and how to solve it, the usual great tutorials and workflows from the Community, online course updates, new docs and more! Happy April!
Jeny De Figueiredo
April 15, 2022
10 minutes read
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