experiment-tracking

A Python framework for creating reproducible, maintainable and modular data science code.

Aim 💫 — easy-to-use and performant open-source ML experiment tracker.

PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡

🏕️ Development environment for AI/ML, based on buildkit

Machine Learning automation and tracking

Visualise your Kedro data and machine-learning pipelines and track your experiments.

Code for Kaggle and Offline Competitions

A Clojure machine learning library

SEML: Slurm Experiment Management Library

Metadata store for Production ML

Deploy MLflow with HTTP basic authentication using Docker

GitHub Action That Retrieves Model Runs From Weights & Biases

2 Lines of code to track ML experiments + EDA + check into Github

Custom ML tracking experiment and debugging tools.

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

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.

Lightning Talk about sacred at PyData Berlin

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.

🔬 Lightweight experiment and configuration manager for small ML/DL projects and Kaggling

Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.