Stay updated with DagsHub’s latest podcast, EU AI Act insights, active learning pipeline tips, case study, and platform enhancements for August 2023. Hello and welcome to the August edition of Pawesome Updates! We’ve been hard at work here at DagsHub to bring you some exciting developments in the world of machine learning and …
Learn how the new version of MLflow supports logging experiments of Large Language Models The rapid development of Large Language Models (LLMs) like Chat GPT, LLAMA 2, and Falcon has revolutionized the Data Science world and introduced a new concept: ״Prompt Engineering״ Prompting involves using input text or questions to guide LLMs in …
LLMOps: Experiment Tracking with MLflow for Large Language Models Read More »
With the release of Data Engine, DagsHub has made it easier to create an Active Learning Pipeline. This tutorial shows how to create one for an image segmentation model using COCO 1K An end-to-end active learning pipeline is something many struggle with. Even large companies with experienced data science teams run into issues. …
Tutorial: Build an Active Learning Pipeline using Data Engine Read More »
The EU AI Act is a draft rule that was passed last month by the European Parliament. Understanding the AI Act today will go a long way to reduce technical debt and will saves months of work in the transition to compliance. Most of us working in the ML and AI industry will …
In this episode, Dean speaks with Yuval Gabay, MLOps Engineer at WSC Sports. They talk about MLOps methodologies, standardizing deployment in the organization, and closing the loop back from production into training. In this episode, I had the pleasure of speaking with Yuval Gabay, MLOps Engineer at WSC Sports. Yuval builds better infrastructure …
⛹️♂️ Large Scale Video ML at WSC Sports with Yuval Gabay Read More »
DagsHub’s Data Engine boosts ML teams’ productivity by simplifying dataset experimentation. Access data efficiently, pinpoint weak points, automate preparation, and refine models effectively. Elevate your ML efforts with seamless data handling. ML teams have a very important core purpose in their organizations – delivering high-quality, reliable models, fast. They are trusted to maintain …
How Creating Training-ready Datasets Faster Can Unleash ML Teams’ Productivity Read More »
