Course overview
Key skills
Course outline
Decision Tree Modeling in Python [5 lessons]
Introduction to Decision Trees 2h
Lesson Objectives- Define decision trees
- Identify the importance of entropy and information gain
Building a Decision Tree 1h
Lesson Objectives- How to build a decision tree
- How the ID3 algorithm works
- How to make predictions using decision trees
Applying Decision Trees 1h
Lesson Objectives- Train a decision tree model using scikit-learn
- Evaluate errors using AUC
- Reduce overfitting with decision trees
Introduction to Random Forests 1h
Lesson Objectives- How to ensemble decision trees to improve prediction quality
- How to introduce variation with bagging
- How to reduce overfitting with random forests
Guided Project: Predicting Bike Rentals 1h
Lesson Objectives- Create new features
- Apply different machine learning models
Projects in this course
Guided Project: Predicting Bike Rentals
Apply decision trees and random forests to predict the number of bike rentals.
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