✨ 7 Best Machine Learning Experiment Logging Tools in 2022 🚀

 


1️⃣ Weights & Biases


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

2️⃣ Neptune


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

3️⃣ Comet


📌 Comet’s machine learning platform integrates with your existing infrastructure and tools
📌You can manage, visualize, and optimize models—from training runs to production monitoring.


4️⃣ MLFlow


📌 MLFlow is an open source platform for the machine learning lifecycle.

5️⃣ Amazon SageMaker


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

6️⃣ Verta.ai


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


7️⃣ Sacred


📌 Sacred is a tool to help you configure, organize, log and reproduce experiments.

 

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