Experiment Tracking
ML experiment tracking and model registries · 5 plugins
Comet ML
Flytekitflytekitplugins-comet-ml
Comet’s machine learning platform integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring. This plugin integrates Flyte with Comet.ml by configuring links between the two platforms.
MLflow
Flytekitflytekitplugins-mlflow
MLflow enables us to log parameters, code, and results in machine learning experiments and compare them using an interactive UI.
Neptune
Flytekitflytekitplugins-neptune
Neptune is the MLOps stack component for experiment tracking. It offers a single place to log, compare, store, and collaborate on experiments and models. This plugin integrates Flyte with Neptune by configuring links between the two platforms.
Weights & Biases
Flytekitflytekitplugins-wandb
The Weights and Biases MLOps platform helps AI developers streamline their ML workflow from end-to-end. This plugin
Weights & Biases
v2Flyte SDK (v2)flyteplugins-wandb
This plugin provides integration between Flyte and Weights & Biases (W&B) for experiment tracking, including support for distributed training with PyTorch Elastic.