How to Track ML Model Training: LightGBM + neptune.ai 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 trainingrn
- Training and validation metrics
- 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 trainingrn
- Pickled model
- Feature importance chart (gain and split)
- Visualized trees
- Trees saved as DataFrame
- Confusion matrix (only for classification problems)
Read the documentation
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