How to Track ML Model Training: LightGBM + Neptune Integration

What will you get with this integration?

LightGBM is a gradient boosting framework that uses tree-based learning algorithms.

Neptune + LightGBM integration, lets you:

• Automatically log many types of metadata during training
  • Training and validation metrics

  • Parameters

  • Feature names, num_features and num_rows for the train set

  • Hardware consumption (CPU, GPU, memory)

  • Stdout and stderr logs

  • Training code and git commit information

• Log model summary after training
  • Pickled model

  • Feature importance chart (gain and split)

  • Visualized trees

  • Trees saved as DataFrame

  • Confusion matrix (only for classification problems)