Python

Moving Local Experiments to the Cloud with Terraform Provider Iterative (TPI) and Docker
Tutorial for easily running experiments in the cloud with the help of Terraform Provider Iterative (TPI) and Docker.

Moving Local Experiments to the Cloud with Terraform Provider Iterative (TPI)
Tutorial for easily moving a local ML experiment to a remote cloud machine with the help of Terraform Provider Iterative (TPI).

Easy Stuctural Refactors to Python Source Code
Simple, hassle-free, dependency-free, AST based source code refactoring toolkit.

(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.

June '20 Community Gems
A roundup of technical Q&A's from the DVC community. This month, we discuss migrating to DVC 1.0, the new pipeline format, and our Python API.

Packaging data and machine learning models for sharing
A virtual poster for SciPy 2020 about sharing versioned datasets and ML models with DVC.

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.

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?

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.