XGBoost and Data Leakage in Machine Learning - Day 14 of 30 Days of ML

Dive into Day 14 of Kaggle's 30 Days of ML Challenge, focusing on XGBoost and data leakage in machine learning. Explore the power of gradient boosting, a technique that dominates many Kaggle competitions and achieves state-of-the-art results on various datasets. Learn how to build and optimize models using XGBoost, and gain insights from a comprehensive tutorial. Understand the critical concept of data leakage, its potential to ruin models in subtle and dangerous ways, and discover effective prevention strategies. Complete hands-on exercises to reinforce your learning and wrap up Kaggle's Intermediate ML Course. Access additional resources, including related videos and a StatQuest tutorial on XGBoost, to deepen your understanding of these essential machine learning concepts.

Kaggle 30 Days of ML (Day 14) - XGBoost, Data Leakage - Learn Python ML in 30 Days