Machine Learning
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray on AWS (Part 2)
Need to setup DVC to work with Ray Cluster on AWS? This tutorial has you covered!
Tutorial: Scalable and Distributed ML Workflows with DVC and Ray (Part 1)
This tutorial introduces you to integrating DVC (Data Version Control) with Ray, turning them into your go-to toolkit for creating automated, scalable, and distributed ML pipelines.
Instant Experiment Tracking: Just Add DVC!
Experiment tracking in DVC with a few lines of Python.
Building a GitOps ML Model Registry with DVC and GTO
Got your data and model versioning down? ✅ Learn how to take your projects to the next level by creating a model registry right in your project's Git repo
Deploy ML models to k8s and SageMaker with a single line of code
MLEM takes the evil configs out of Kubernetes and SageMaker to make your life easier just in time for Halloween 🎃
Productionize your models with MLEM in a Git-native way
Introducing MLEM - one tool to run your models anywhere.
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.
