[P] I trained an XGBoost model with DuckLake and ADBC
Reddit - Machine Learning
1 min read
Article
Summary
The article discusses training an XGBoost model using Apache ADBC and DuckLake, highlighting efficient data handling and model training without scikit-learn.
Why It Matters
This content is relevant for data scientists and machine learning practitioners as it explores innovative methods for handling large datasets and model training in a memory-efficient manner. The use of Apache ADBC and DuckLake represents a growing trend in leveraging lakehouse architectures for advanced data processing.
Key Takeaways
- XGBoost can efficiently utilize Arrow tables for model training.
- Apache ADBC allows for streaming data larger than memory.
- Custom functions can replace scikit-learn for data splitting.
- DuckLake architecture enhances data handling capabilities.
- Memory overhead is minimized when using Arrow tables.
You've been blocked by network security.To continue, log in to your Reddit account or use your developer tokenIf you think you've been blocked by mistake, file a ticket below and we'll look into it.Log in File a ticket
