Tutorial
MLEM + Modal + nanoGPT
Train and deploy your own GPT model in 2 easy steps!
Deploy Computer Vision Models Faster and Easier
One command to serve CV models from your laptop in the cloud 🚀
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
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.
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.
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.
Syncing Data to GCP Storage Buckets
We're going to set up a GCP storage bucket remote in a DVC project.
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.