Data Science and Analytics

Tutorial: How to Setup SageMaker for Machine Learning CI/CD Pipelines

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   ​ Learn how to setup AWS SageMaker environment to create and run custom CI/CD pipelines for Machine Learning​ ​ With the advent of “bigger and badder” machine learning models and their usage in production, it has become necessary to orchestrate the entire MLOps process. This process is often time-consuming, repetitive, and resource-dependent. The issue is …

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LLMOps: Experiment Tracking with MLflow for Large Language Models

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   ​ 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 …

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Tutorial: Build an Active Learning Pipeline using Data Engine

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   ​ 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. …

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⛹️‍♂️ Large Scale Video ML at WSC Sports with Yuval Gabay

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   ​ 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 …

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How Creating Training-ready Datasets Faster Can Unleash ML Teams’ Productivity

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   ​ 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 …

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