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    Tutorial

    Automate Your ML Pipeline: Combining Airflow, DVC, and CML for a Seamless Batch Scoring Experience
    This tutorial shows you how to supercharge your batch scoring workflow by harnessing the power of Aiflow, DVC and CML.
    • Mikhail Rozhkov
    • Mar 22, 202310 min read
    MLEM + Modal + nanoGPT
    Train and deploy your own GPT model in 2 easy steps!
    • Mike Sveshnikov
    • Feb 08, 20232 min read
    Deploy Computer Vision Models Faster and Easier
    One command to serve CV models from your laptop in the cloud 🚀
    • Mike Sveshnikov
    • Jan 19, 20233 min read
    Building a GitOps ML Model Registry with DVC and GTO
    Got your data and model versioning down? ✅ Learn how to take your projects to the next level by creating a model registry right in your project's Git repo
    • Alexander Guschin
    • Dec 07, 20229 min read
    From Jupyter Notebook to DVC pipeline for reproducible ML experiments
    In this guide we will take a Jupyter Notebook and use Papermill to turn it into a simple, one-stage DVC pipeline.
    • Rob de Wit
    • Oct 24, 20229 min read
    CML Cloud Runners for Model Training in Bitbucket Pipelines
    Use CML from a Bitbucket pipeline to provision an AWS EC2 instance and (re)train a machine learning model.
    • Rob de Wit
    • Sep 06, 20225 min read
    Serving Machine Learning Models with MLEM
    Once you have a machine learning model that's ready for production, getting it out can be complicated. In this tutorial, we're going to use MLEM to deploy a model as a web API.
    • Milecia McGregor
    • Jul 19, 20225 min read
    Syncing Data to GCP Storage Buckets
    We're going to set up a GCP storage bucket remote in a DVC project.
    • Milecia McGregor
    • Jul 06, 20224 min read
    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, 20224 min read