MLflow
Open-source platform for managing the lifecycle of machine learning projects.
MLflow is an open-source platform that supports the lifecycle of machine learning projects. It helps log experiments in a traceable way, capture parameters and metrics, package models and make them available for production use.
MLflow is divided into several components, including Tracking for logging training runs, a Registry for versioning models, and features for standardized packaging and serving. The framework is language- and library-agnostic and can be integrated into existing ML workflows.
What Provimedia uses it for
Provimedia uses MLflow in AI development to document training runs traceably and manage model versions in a structured way.
Want to use MLflow for your project?
In a free conversation, let's find out how we can implement this for you.
More from AI & machine learning
Anthropic Claude
Family of large language models from the AI company Anthropic.
Learn moreApache Airflow
Open-source platform for authoring, scheduling and monitoring workflows.
Learn moreCUDA
NVIDIA's parallel computing platform for using GPUs for general-purpose computation.
Learn moreElevenLabs
AI platform for synthesizing natural-sounding speech from text.
Learn moreHugging Face
Platform and libraries for pretrained AI models and datasets.
Learn moreKeras
High-level API for building and training neural networks.
Learn moreLangChain
Open-source framework for developing applications based on large language models.
Learn moreNLTK
Established Python library for natural language processing.
Learn more