Try it yourself! Explore the demo Model Registry to test drive Iterative Studio's MR.
Product updates, news, tutorials, integrations, and deep dives.
Tutorial
Running Collaborative Experiments
Sharing experiments with teammates can help you build models more efficiently.
Adding Data to Build a More Generic Model
You can easily make changes to your dataset using DVC to handle data versioning. This will let you extend your models to handle more generic data.
Using Experiments for Transfer Learning
You can work with pretrained models and fine-tune them with DVC experiments.
Tuning Hyperparameters with Reproducible Experiments
Using DVC, you'll be able to track the changes that give you an ideal model.
Cloud Data Sync Methods and Benchmark: DVC vs Rclone
DVC 1.0 optimized data synchronization to and from remote storage. Here's how we did it.
November ’20 Heartbeat
Catch our monthly updates- featuring new video docs and talks, new jobs at DVC, and must-read contributions from the community about MLOps, data science with R, and ML in production.
October ’20 Heartbeat
This month, hear about our international talks, new video docs on our YouTube channel, and the best tutorials from our community.
CML self-hosted runners on demand with GPUs
Use your own GPUs with GitHub Actions & GitLab for continuous machine learning.
NEW VIDEO! 🎥 MLOps Tutorial #1:
Intro to continuous integration for ML
A video tutorial about using continuous integration in data science and machine learning projects. This tutorial shows how to use GitHub Actions and Continuous Machine Learning (CML) to create your own automated model training and evaluation system.
