End-to-End Computer Vision API, Part 3: Remote Experiments & CI/CD For Machine Learning
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.
Alex Kim
Alex Kim
May 9, 2022
7 minutes read
Training and saving models with CML on a dedicated AWS EC2 runner (part 2)
Use CML to automatically retrain a model on a provisioned AWS EC2 instance and export the model to a DVC remote storage on Google Drive.
Rob de Wit
Rob de Wit
May 6, 2022
8 minutes read
End-to-End Computer Vision API, Part 1: Data Versioning and ML Pipelines
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.
Alex Kim
Alex Kim
May 3, 2022
7 minutes read
April ’22 Community Gems
A roundup of technical Q&As from the DVC and CML community. This month: CML updates, working with multiple datasets, using DVC stages, and more.
Milecia McGregor
Milecia McGregor
April 28, 2022
4 minutes read
Training and saving models with CML on a self-hosted AWS EC2 runner (part 1)
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.
Rob de Wit
Rob de Wit
April 26, 2022
8 minutes read
April ’22 Heartbeat
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
Jeny De Figueiredo
April 15, 2022
10 minutes read

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