There are 12 repositories under experiment-tracking topic.
A Clojure machine learning library
Deploy MLflow with HTTP basic authentication using Docker
Experiment tracking server focused on speed and scalability
Metadata store for Production ML
A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management 🚀
GitHub Action That Retrieves Model Runs From Weights & Biases
MLOps for deploying a Credit Risk model
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.
An end to end ML project. Using MLflow for experiment tracking and model registry. Prefect for workflow orchestration. S3 for artifacts storage. AWS Lambda/ ECR for serverless model serving. AWS REST API gateway as endpoint to lambda function. GitHub Actions for CI/CD.
A curated list of awesome open source and commercial MLOps platforms 🚀
A demonstration of how DVC and MLFlow can be used in the task of data relabeling
Lightning Talk about sacred at PyData Berlin
create a robust, simple, effecient, and modern end to end ML Batch Serving Pipeline Using set of modern open-source/free Platforms/Tools
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.
A SageMaker Experiment logger class for PyTorch Lightning
Python library for programatic interaction with Coretex experiment tracking and orchestration server.
Faculty platform plugin for MLflow
🔬 Lightweight experiment and configuration manager for small ML/DL projects and Kaggling
Experiment tracking with MLFlow.
A powerful and versatile data analysis platform infrastructure framework designed to help data analysts of every kind achieve reproducibility and streamline their workflows. It is entirely technology agnostic, making it suitable for any tool or language.
Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.
Track model training experiments with MLflow and FiftyOne!
This project applies machine learning models to predict BMI categories based on individual physical attributes, utilizing MLflow for experiment tracking and model management, with integration into DagsHub for collaborative data science workflows. It showcases the power of MLflow in enhancing model lifecycle management and reproducibility.