Introduction to XGBoost

This course introduces the concept of Extreme Gradient Boosting Classifier that clearly lays out improvements of the algorithm over other Boosting methods.

  • icon-data 2 Data Cases
  • icon-reading 1 Reading
  • icon-quiz 1 Quiz
Introduction to XGBoost
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    Difficulty: Advanced

    Prior education or professional experience required

  • Asset 1
    Duration: Approximately 5 hours

Course Overview

  • The course familiarizes the learner with the concept of Boosting in Machine Learning emphasizing on Extreme Gradient Boosting algorithm.
  • Learn how the algorithm can be applied for both Regression and Classification tasks.
  • The course demonstrates hyper parameter tuning for XGBoost algorithm for performance improvement.
  • Learn the methods to evaluate an XG boost model.

What’s included

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Lifetime Access

Access this project for life once completed

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Flexible Scheduling

Start learning online immediately, at your own pace

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Desktop Only

We recommend completing this project on a desktop

Skills you will learn

User Interface

Working of XG Boost Algorithm

Features of XG Boost Algorithm

Hyperparameters in XG Boost

XG Boost Model Evaluation

Data Science

Data Analysis

Advanced Machine Learning

Boosting

Associated Learning Tracks

Syllabus

This course introduces the concept of Extreme Gradient Boosting Classifier that clearly lays out improvements of the algorithm over other Boosting methods

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