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All LessonsFree Lessons (5)

Welcome to the Course

Course Expectations Machine Learning Is Predictive Analytics The Course Datasets Quiz: Data Basics

Supervised Learning

What Is Machine Learning?Forms of Supervised Learning Why Decision Trees?Decision Tree Intuition Overfitting Intuition Model Tuning Intuition Quiz: Machine Learning Concepts

Classification Tree Math

Gini Impurity Gini Change Classification Tree Training Example Many Categories Impurity Numeric Feature Impurity Quiz: Classification Tree Math

Using Classification Trees in R

Exploratory Data Analysis—Profiling Exploratory Data Analysis: Visualization Introducing tidymodels Crafting the Recipe Specify the Algorithm and Workflow Fitting the Model Quiz: Fitting Models

Introducing the Bias-Variance Tradeoff

Underfitting and Overfitting The Bias-Variance Tradeoff Quiz: Underfitting, Overfitting, and the Bias-Variance Tradeoff

Model Tuning

Cross-Validation Model Tuning Intuition 201 Controlling Complexity Pruning Classification Trees

Model Tuning with tidymodels

Measuring Model Accuracy Performing Cross-Validation Tuning a Classification Tree Visualizing a Tuned Classification Tree Quiz: Model Tuning

Feature Engineering

Feature Engineering Intuition Information Leakage Decision Boundaries Engineering Features for Decision Trees Missing Data Quiz: Feature Engineering

Regression Trees

Regression Tree Basics Numeric Feature SSE Many Categories SSE Regression Trees with tidymodels Quiz: Regression Trees

The Random Forest Algorithm

Decision Trees and Ensembles Bagging Feature Randomization Quiz: Random Forests

Using Random Forests

Random Forests with tidymodels Feature Importance Tuning Random Forests Preparing the Test Dataset Making Predictions Testing the Titanic Dataset Quiz: Using Random Forests

Gradient Boosting Trees

How Gradient Boosting Works

Gradient Boosting with XGBoost

Using XGBoost with tidymodels

Tuning XGBoost with tidymodels

Evaluating XGBoost with tidymodels

Continuing Your Journey

Project

Credit Card Fraud Detection using the R Language

Data Science with R: Decision Trees and Random Forests/

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Quiz: XGBoost

Quiz: XGBoost

Test what you’ve learned about XGBoost.

We'll cover the following...

Technical Quiz

1.

(True or False) The XGBoost algorithm adds trees to the ensemble where each tree learns patterns in the errors of the previous tree.

A.

True

B.

False

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