A Gentle Introduction to XGBoost for Applied Machine Learning

Last Updated on April 22, 2020

XGBoost is an algorithm that has recently been dominating applied machine learning and Kaggle competitions for structured or tabular data.

XGBoost is an implementation of gradient boosted decision trees designed for speed and performance.

In this post you will discover XGBoost and get a gentle introduction to what is, where it came from and how you can learn more.

After reading this post you will know:

• What XGBoost is and the goals of the project.
• Why XGBoost must be a part of your machine learning toolkit.
• Where you can learn more to start using XGBoost on your next machine learning project.

Kick-start your project with my new book XGBoost With Python, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

A Gentle Introduction to XGBoost for Applied Machine Learning
Photo by Sigfrid Lundberg, some rights reserved.