Data Version Control
PulseAugur coverage of Data Version Control — every cluster mentioning Data Version Control across labs, papers, and developer communities, ranked by signal.
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Kubernetes and DVC form foundation for ML pipelines
This article introduces the first part of a series on building machine learning pipelines using Kubernetes and DVC. It focuses on establishing an on-premises Kubernetes foundation for these pipelines. The series aims to…
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MLOps guide explains DVC data restoration on new clones
This article details how to restore data using the Data Version Control (DVC) tool on a newly cloned repository. It serves as a practical guide for developers working with machine learning projects that utilize DVC for …
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DVC configured for S3-compatible remote storage in MLOps challenge
This article details how to configure DVC (Data Version Control) to use S3-compatible remote storage. It serves as a practical guide for MLOps practitioners looking to manage large datasets and models efficiently. The p…
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MLOps Challenge Details Git to DVC Data Migration
This series details the process of migrating large datasets from Git to Data Version Control (DVC) as part of a 100 Days of MLOps challenge. The articles focus on the practical steps and benefits of using DVC for data v…
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ML practitioners can version datasets without specialized tools
This article proposes a practical, tool-free method for versioning datasets in machine learning to ensure reproducibility. It argues that maintaining a consistent data contract between pipelines and training processes i…
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South African universities urged to prepare for Gen-AI adoption
Generative AI is already present in South African universities, with students and some staff utilizing it without clear institutional policies. Decision-makers must prepare for AI adoption rather than merely reacting to…
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Dynamic Vine Copulas detect time-varying higher-order interactions in data
Researchers have introduced Dynamic Vine Copulas (DVC), a novel framework designed to detect and quantify time-varying higher-order interactions in multivariate systems. Unlike traditional methods that focus on correlat…
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AWS and DVC integrate for end-to-end ML model lineage tracking
A new solution integrates DVC with Amazon SageMaker MLflow Apps to provide end-to-end lineage tracking for machine learning models. This addresses the challenge of tracing models back to their exact training data and co…