Join us in this hands-on video tutorial as we explore the basics and beyond of XGBoost. We'll introduce you to gradient-boosting principles like initialization, loss functions, and decision trees, and guide you through data preparation, parameter tuning, and model evaluation. See a real-world implementation in action and learn how to deploy your XGBoost model for real-world applications. Whether you're starting or looking to refine your skills, this video will provide you with the knowledge and tools to excel in XGBoost.
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🏁 Topics Covered:
00:00:00 Beginning
00:00:59 Introduction to XGBoost
00:06:28 Attributes, Benefits, and Limitations of XGBoost
00:14:16 Introduction to Gradient Boosting
00:16:45 XGBoost vs Gradient Boost vs Ada Boosting
00:23:36 XGBoost vs Random Forest
00:26:10 XGBoost - Working
00:33:41 Steps to Perform XGBoost
00:38:04 XGBoost Hands-on
01:04:30 XGBoost - Summary
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