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Experiment tracking for training ML models
A fully open-source, performant and actionable Weights & Biases alternative that saves you money. Check out our story here! https://www.reddit.com/r/mlopai/comments/1kkc9jp/mlopai_an_efficient_free_and_opensource/
mlop is an open source MLOps platform focused on experiment tracking for machine learning. It tracks experiments, parameters, gradients, and performance, with real-time alerts and integrations to fit into existing codebases and workflows.
The product provides experiment tracking and reproducibility features, including real-time tracking of model parameters and gradients, performance metrics over time, and uncommitted file/version tracking. It integrates with users' code bases and ML pipelines, supports media tracking and alerting, and offers a self-hosted option with enterprise features. Pricing includes a free tier and a pro/enterprise path, with the option for custom plans and a self-hosted installation.
Who it’s for: machine learning engineers, ML researchers, data science teams, startups and enterprises building and deploying ML models
Founding/open source tool with YC backing, pricing page and self-hosted/enterprise options; mentions of community-driven development and enterprise features
Growth Operations Data Platform
Independent AI evaluations lab
