Iterative Blog
Find here DataChain and DVC news, findings, interesting reads, community takeaways, deep dive into machine learning workflows from data versioning and processing to model productionization.
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.
March ’19 DVC❤️Heartbeat
The very first issue of the DVC Heartbeat! News, links, Discord discussions from the community.
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.
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?
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.
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.
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.
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.