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    DVC AI Blog

    Find here DVC AI news, findings, interesting reads, community takeaways, deep dive into machine learning workflows from data versioning and processing to model productionization.

    September '20 Community Gems
    A roundup of technical Q&A's from the DVC community. This month, we discuss customizing your DVC plots, the difference between external dependencies and outputs, and how to save models and data in CI.
    • Elle O'Brien
    • Sep 28, 20205 min read
    September ’20 Heartbeat
    This month, catch us on the Software Engineering Daily Podcast, check out our favorite DVC and CML tutorials and projects, and celebrate 1000 YouTube subscribers!
    • Elle O'Brien
    • Sep 09, 20203 min read
    August '20 Community Gems
    A roundup of technical Q&A's from the DVC community. This month, we discuss using CI/CD to validate models, advanced DVC pipeline scenarios, and how CML adds pictures to your GitHub and GitLab comments.
    • Elle O'Brien
    • Aug 27, 20205 min read
    August ’20 Heartbeat
    Catch our monthly updates- featuring the CML release, DVC meetup recap, a new video tutorial series, and the best reading about pipelines and DataOps.
    • Elle O'Brien
    • Aug 10, 20205 min read
    CML self-hosted runners on demand with GPUs
    Use your own GPUs with GitHub Actions & GitLab for continuous machine learning.
    • David G Ortega
    • Aug 07, 20203 min read
    July '20 Community Gems
    A roundup of technical Q&A's from the DVC community. This month, we discuss getting started with CML, configuring your DVC cache, and how to request a tutorial video.
    • Elle O'Brien
    • Jul 31, 20205 min read
    (Tab) Complete Any Python Application in 1 Minute or Less
    We've made a painless tab-completion script generator for Python applications! Find out how to take advantage of it in this blog post.
    • Casper da Costa-Luis
    • Jul 27, 20203 min read
    NEW VIDEO! 🎥 MLOps Tutorial #1: Intro to continuous integration for ML
    A video tutorial about using continuous integration in data science and machine learning projects. This tutorial shows how to use GitHub Actions and Continuous Machine Learning (CML) to create your own automated model training and evaluation system.
    • Elle O'Brien
    • Jul 24, 20201 min read
    What data scientists need to know about DevOps
    A philosophical and practical guide to using continuous integration (via GitHub Actions) to build an automatic model training system.
    • Elle O'Brien
    • Jul 16, 20209 min read