Product updates, news, tutorials, integrations, and deep dives.
DVC
Turn Visual Studio Code into a machine learning experimentation platform with the DVC extension
Today we are releasing the DVC extension, which brings a full ML experimentation platform to Visual Studio Code.
Syncing Data to Azure Blob Storage
We're going to set up an Azure Blob Storage remote in a DVC project.
Syncing Data to AWS S3
We're going to set up an AWS S3 remote in a DVC project.
May '22 Heartbeat
Monthly updates are here! You will find a link to Chip Huyen's new book, great guides and frameworks on the iterative nature of AI, tons of company news, Dmitry on TFIR, beyond machine learning use cases and more! Welcome to May!
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.
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.
End-to-End Computer Vision API, Part 2: Local Experiments
In part 1, we talked about effective management and versioning of large datasets and the creation of reproducible ML pipelines.
Here we'll learn about experiment management: generation of many experiments by tweaking configurations and hyperparameters; comparison of experiments based on their performance metrics; and persistence of the most promising ones
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.
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!