Product updates, news, tutorials, integrations, and deep dives.
Scalable PDF Document Processing with DataChain and Unstructured.io
Extract and parse text from documents and create vector embeddings in a scalable and distributed way (and less than 70 lines of code).
You Do the Math: Fine Tuning Multimodal Models (CLIP) to Match Cartoon Images to Joke Captions
Learn how to fine tune multimodal models like CLIP to match images to text captions.
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray on AWS (Part 2)
Need to setup DVC to work with Ray Cluster on AWS? This tutorial has you covered!
Announcing DataChain
Introducing DataChain - a new open-source tool to curate and process unstructured data using local ML models, and LLM calls.
The DVC 3.0 Stack: Beyond the Command Line
DVC 3.0 introduces a stack of tools outside the command line to bring it closer to
where you work (in code, IDE, web) while also focusing on DVC fundamentals.
Organize Your Storage with DVC Cloud Versioning
DVC cloud versioning makes it easy to take full advantage of your cloud
provider’s built-in versioning capabilities.
As GenAI Fever Fades - Time to Prioritize Robust Engineering Over Overblown Promises
Improved Engineering and Data Management will be what carries GenAI into maturity
Scalable PDF Document Processing with DataChain and Unstructured.io
Extract and parse text from documents and create vector embeddings in a scalable and distributed way (and less than 70 lines of code).
Post-modern AI Data Stack
How and Why Generative AI will change the modern data stack.
Dataset Factory - A Toolchain for Generative Computer Vision Datasets
Learn about our latest approach to mastering your Unstructured Data and metadata.
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray on AWS (Part 2)
Need to setup DVC to work with Ray Cluster on AWS? This tutorial has you covered!
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray (Part 1)
This tutorial introduces you to integrating DVC (Data Version Control) with Ray, turning them into your go-to toolkit for creating automated, scalable, and distributed ML pipelines.
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.
Real-time visualization of Computer Vision model training with DVC and Iterative Studio
Save time and resources by tracking your deep learning experiments in real-time with DVC and Iterative Studio.
December '22 Heartbeat
Monthly updates are here! Great content from the Community, including a DVC extension for VS Code tutorial, sweet MLOps guide, framework agnostic ml pipeline with DVC and non-Python apps to integrate ML models with MLEM. Welcome to December!
Turn Your Favorite IDE into a Full Machine Learning Experimentation Platform
DVC extension enables you to run, track and manage ML experiments without leaving VS Code.
The DVC 3.0 Stack: Beyond the Command Line
DVC 3.0 introduces a stack of tools outside the command line to bring it closer to
where you work (in code, IDE, web) while also focusing on DVC fundamentals.
Instant Experiment Tracking: Just Add DVC!
Experiment tracking in DVC with a few lines of Python.