✨ 7 Best Machine Learning Experiment Logging Tools in 2022 πŸš€

 


1️⃣ Weights & Biases


πŸ“Œ Weights & Biases is the developer-first MLOps platform for building better models faster with experiment tracking, dataset versioning, and model management.

2️⃣ Neptune


πŸ“Œ Neptune is a tool for Experiment tracking and model registry for production teams.
πŸ“Œ You can log, store, query, display, organize and compare all your model metadata in a single place.

3️⃣ Comet


πŸ“Œ Comet’s machine learning platform integrates with your existing infrastructure and tools
πŸ“ŒYou can manage, visualize, and optimize modelsβ€”from training runs to production monitoring.


4️⃣ MLFlow


πŸ“Œ MLFlow is an open source platform for the machine learning lifecycle.

5️⃣ Amazon SageMaker


πŸ“Œ Amazon SageMaker is used for complete control of the ML development lifecycle.
πŸ“Œ You can manage production models, associate metadata, and manage versions and approval status of models with the SageMaker registry.

6️⃣ Verta.ai


πŸ“Œ Verta.ai is an MLOps platform to simplify your AI/ML model management & operations at scale.


7️⃣ Sacred


πŸ“Œ Sacred is a tool to help you configure, organize, log and reproduce experiments.

 

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