Data Version Control in Real Life

We write about machine learning workflow. From data versioning and processing to model productionization. We share our news, findings, interesting reads, community takeaways.
DVC project ideas for Google Season of Docs 2019
DVC.org is applying for Google Season of Docs — a new and unique program sponsored by Google that pairs technical writers with open source projects to collaborate on the open source project documentation.
  • Svetlana Grinchenko
  • Apr 23, 20198 min read
April ’19 DVC❤️Heartbeat
DVC creator Dmitry Petrov is giving a talk on PyCon 2019 🎤, new DVC logo design, new Discord discussions, interesting reads that caught our eye, and everything along the way.
  • Svetlana Grinchenko
  • Apr 18, 201914 min read
March ’19 DVC❤️Heartbeat
The very first issue of the DVC Heartbeat! News, links, Discord discussions from the community.
  • Svetlana Grinchenko
  • Mar 05, 20195 min read
ML best practices in PyTorch dev conf 2018
In the Machine Learning (ML) field tools and techniques for best practices are just starting to be developed.
  • Dmitry Petrov
  • Oct 18, 20184 min read
Best practices of orchestrating Python and R code in ML projects
What is the best way to integrate R and Python languages in one data science project? What are the best practices?
  • Marija Ilić
  • Sep 26, 201710 min read
ML Model Ensembling with Fast Iterations
Here we'll talk about tools that help tackling common technical challenges of building pipelines for the ensemble learning.
  • George Vyshnya
  • Aug 23, 201712 min read
Data Version Control in Analytics DevOps Paradigm
Why DevOps matters in data science, what specific challenges data scientists face in the day to day work, and how do we setup a better environment for the team.
  • George Vyshnya
  • Jul 27, 20175 min read
R code and reproducible model development with DVC
There are a lot of example on how to use Data Version Control (DVC) with a Python project. In this document I would like to see how it can be used with a project in R.
  • Marija Ilić
  • Jul 24, 201715 min read
How Data Scientists Can Improve Their Productivity
Data science and machine learning are iterative processes. It is never possible to successfully complete a data science project in a single pass.
  • Dmitry Petrov
  • May 15, 20176 min read
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