new machine learning course: Extreme Gradient Boosting!

Want to learn to use state-of-the-art models on real-world datasets? Learn how to use this powerful library alongside pandas and scikit-learn to build and tune supervised learning models. You'll work with real-world datasets to solve classification as well as regression problems. [DataCamp]( New Machine Learning Course! [ ]( [Play Now]( [ ]( Extreme Gradient Boosting with XGBoost Taught by Sergey Fogelson, VP of Analytics and Measurement Sciences, Viacom Do you know the basics of supervised learning and want to learn to use state-of-the-art models on real-world datasets? Gradient boosting is currently one of the most popular techniques for efficient modeling of tabular datasets of all sizes. XGboost is a very fast, scalable implementation of gradient boosting that has taken data science by storm. [Start Learning]( Extreme Gradient Boosting with XGBoost: What You'll Learn Chapter 1: [Classification with XGBoost]( This chapter will introduce you to the fundamental idea behind XGBoost - boosted learners. Chapter 2: [Regression with XGBoost]( After a brief review of supervised regression, you'll apply XGBoost to the regression task of predicting house prices in Ames, Iowa. Chapter 3: [Fine-tuning your XGBoost model]( This chapter will teach you how to make your XGBoost models as performant as possible. Chapter 4: [Using XGBoost in pipelines]( Take your XGBoost skills to the next level by incorporating your models into two end-to-end machine learning pipelines. [Play Now]( [DataCamp] [DataCamp]( DataCamp Inc. | 350 Fifth Avenue | Suite 7730 | New York, NY 10118 [Facebook] [Facebook]( [Twitter] [Twitter]( [LinkedIn] [LinkedIn]( [YouTube] [YouTube]( [Unsubscribe](