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.
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Updated
May 15, 2024 - Python
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.
FinOps and MLOps platform to run ML/AI and regular cloud workloads with optimal performance and cost.
Visualise your Kedro data and machine-learning pipelines and track your experiments.
Code for Kaggle and Offline Competitions
A powerful and easy to use Python framework for experiment tracking and incremental computing
A Clojure machine learning library
SEML: Slurm Experiment Management Library
Deploy MLflow with HTTP basic authentication using Docker
Experiment tracking server focused on speed and scalability
Metadata store for Production ML
More light-weight pytorch experiment management library!
GitHub Action That Retrieves Model Runs From Weights & Biases
A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management 🚀
2 Lines of code to track ML experiments + EDA + check into Github
MLOps for deploying a Credit Risk model
Tutorial on experiment tracking and reproducibility for Machine Learning projects with DVC
Custom ML tracking experiment and debugging tools.
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.
Add a description, image, and links to the experiment-tracking topic page so that developers can more easily learn about it.
To associate your repository with the experiment-tracking topic, visit your repo's landing page and select "manage topics."