Главная
Study mode:
on
1
Introduction
2
Overview
3
Feature Engineering
4
Early stopping
5
Results
6
Predictions
7
Conclusion
Description:
Learn to implement xgboost modeling with early stopping for efficient and accurate predictions using animal shelter data from #SLICED. Explore feature engineering techniques, analyze results, and generate predictions in this 31-minute screencast. Follow along with the provided code to enhance your understanding of machine learning concepts and their practical applications in real-world scenarios.

Tune XGBoost With Early Stopping to Predict Shelter Animal Status

Julia Silge
Add to list
00:00
-01:25