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    MLOps

    Adding Data to Build a More Generic Model
    You can easily make changes to your dataset using DVC to handle data versioning. This will let you extend your models to handle more generic data.
    • Milecia McGregor
    • Oct 05, 20217 min read
    Using Experiments for Transfer Learning
    You can work with pretrained models and fine-tune them with DVC experiments.
    • Milecia McGregor
    • Aug 24, 202112 min read
    Tuning Hyperparameters with Reproducible Experiments
    Using DVC, you'll be able to track the changes that give you an ideal model.
    • Milecia McGregor
    • Jul 19, 20218 min read
    Introducing DVC Studio
    🚀 We are excited to release DVC Studio, the online UI for DVC and CML. Use DVC Studio for ML versioning, visualization, teamwork and no-code automation on top of DVC and Git. Read all about the exciting features and watch videos to get started quickly.
    • Tapa Dipti Sitaula
    • Jun 02, 20214 min read
    May ’21 Heartbeat
    Monthly updates are here! We've hit 30 team members! MLOps learning opportunities, tutorials with integrations, conference videos, Discord server growth, and more!
    • Jeny De Figueiredo
    • May 21, 20215 min read
    Git Custom References for ML Experiments
    In DVC 2.0, we’ve introduced a new feature set aimed at simplifying the versioning of lightweight ML experiments. In this post, we’ll dive into how exactly these new experiments work.
    • Peter Rowlands
    • Apr 19, 20216 min read
    April ’21 Heartbeat
    Monthly updates are here! Loads from the Community, use cases, videos, 5 new hires, and more!
    • Jeny De Figueiredo
    • Apr 16, 20213 min read
    March ’21 Heartbeat
    Monthly updates are here! News, use cases, videos, journal publications and more!
    • Jeny De Figueiredo
    • Mar 15, 20213 min read