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Arize and Neptune are MLOps tools that aim to improve connected, but different parts of your ML pipeline and ML workflow. Arize helps you visualize your production model performance, understand drift & data quality issues. Neptune logs, stores, displays, and compares all your MLOps metadata for better experiment tracking. With Arize and Neptune, you will be able to train the best model, and pre-launch validate your model, and compare production performances of those models. Read the full blog here.

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Tutorial Notebook

We have set up a very basic example using Neptune with Arize.

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✔️ Steps for this Walkthrough Notebook

  1. Initialize Neptune and set-up Arize client
  2. Logging training callbacks to Neptune
  3. Logging training and validation records to Arize
  4. Storing and versioning model weights with Neptune
  5. Logging and versioning model in production with Arize
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Google Colaboratory