Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

Code for Kaggle and Offline Competitions

SEML: Slurm Experiment Management Library

PyTorch Template for DL projects

Metadata store for Production ML

More light-weight pytorch experiment management library!

GitHub Action That Retrieves Model Runs From Weights & Biases

The Python Component System (PCS) is an API and CLI for building, running, and sharing Python code. AgentOS is a set of libraries built on top of PCS that make it easy to build, run, and share agents that use Reinforcement Learning.

Python’s delightfully modular experiment tracker for MLOps

Lightweight and modular MLOps library targeted at small teams or individuals

Tutorial on experiment tracking and reproducibility for Machine Learning projects with DVC

An MLOps workflow for training, inference, experiment tracking, model registry, and deployment.

Custom ML tracking experiment and debugging tools.

Build ML pipelines with smart caching and remote execution. Develop locally, deploy to HPC clusters instantly. Track with Aim. 🎯

A demonstration of how DVC and MLFlow can be used in the task of data relabeling

create a robust, simple, effecient, and modern end to end ML Batch Serving Pipeline Using set of modern open-source/free Platforms/Tools

Pythonic, type-safe search space configuration for HPO (hyperparameter optimization), NAS (neural architecture search), and ML experiment tracking. Define complex search spaces with conditional parameters, automatic validation, and zero boilerplate. Pydantic-based, Optuna-ready to nail hyperparameter tuning.

CmdInterface enables detailed logging of command line and python experiments in a very lightweight manner (coding wise). It wraps your command line or python function calls in a few lines of python code and logs everything you might need to reproduce the experiment later on or to simply check what you did a couple of years ago.