Find here DataChain and DVC news, findings, interesting reads, community takeaways, deep dive into machine learning workflows from data versioning and processing to model productionization.
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.
Ensuring your machine learning models remain precise and efficient as time progresses, and verifying that your data consistently reflects the real-world scenario.
This post describes a production ML pipeline for fine-tuning large language models using DVC, SkyPilot, HuggingFace Transformers, and quantization techniques.