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

1littlecoder via YouTube

Overview

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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.

Syllabus

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

Taught by

1littlecoder

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