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Resources » How to Track ML Model Training: XGBoost + Neptune Integration

How to Track ML Model Training: XGBoost + Neptune Integration

What will you get with this integration?

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible, and portable. It implements machine learning algorithms under the Gradient Boosting framework.

Neptune + XGBoost integration, lets you automatically log many types of metadata during training:

  • Metrics
  • Parameters
  • Learning rate
  • Pickled model
  • Visualizations (feature importance chart and tree visualizations)
  • Hardware consumption (CPU, GPU, memory)
  • Stdout and stderr logs
  • Training code
  • Git commit information

Read the documentation

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