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    Product updates, news, tutorials, integrations, and deep dives.

    Tutorial

    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
    Packaging data and machine learning models for sharing
    A virtual poster for SciPy 2020 about sharing versioned datasets and ML models with DVC.
    • Elle O'Brien
    • Jun 26, 20205 min read
    AITA for making this? A public dataset of Reddit posts about moral dilemmas
    Releasing an open natural language dataset based on r/AmItheAsshole.
    • Elle O'Brien
    • Feb 17, 20208 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, 20176 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, 20178 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, 20179 min read