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    Data Version Control in Real Life

    We write about machine learning workflow. From data versioning and processing to model productionization. We share our news, findings, interesting reads, community takeaways.
    Syncing Data to Azure Blob Storage
    We're going to set up an Azure Blob Storage remote in a DVC project.
    • Milecia McGregor
    • Jun 13, 20226 min read
    Productionize your models with MLEM in a Git-native way
    Introducing MLEM - one tool to run your models anywhere.
    • Alexander Guschin
    • Jun 01, 20227 min read
    Syncing Data to AWS S3
    We're going to set up an AWS S3 remote in a DVC project.
    • Milecia McGregor
    • May 31, 20225 min read
    May '22 Community Gems
    A roundup of technical Q&A's from the DVC and CML communities. This month: working with CML and GCP, DVC data and remotes, DVC pipelines and setups, and more.
    • Milecia McGregor
    • May 26, 20225 min read
    Moving Local Experiments to the Cloud with Terraform Provider Iterative (TPI) and Docker
    Tutorial for easily running experiments in the cloud with the help of Terraform Provider Iterative (TPI) and Docker.
    • Casper da Costa-Luis
    • May 24, 20224 min read
    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!
    • Jeny De Figueiredo
    • May 16, 202215 min read
    Moving Local Experiments to the Cloud with Terraform Provider Iterative (TPI)
    Tutorial for easily moving a local ML experiment to a remote cloud machine with the help of Terraform Provider Iterative (TPI).
    • Maria Khalusova
    • May 12, 20229 min read
    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
    • May 09, 20229 min 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
    • May 06, 20227 min read
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