Wednesday

Objectives

• Learn about supervised classification and how to use data you have to predict new data.
• Get introduced to unsupervised classification algorithms and how they’re used
• Build and understand the Decision Tree Classifier

Readings

• The first 3 sections of this chapter
• Decision Tree Learning
• Sections 3.1 through 3.3 of this chapter
• How to Implement the Decision Tree Algorithm from Scratch in Python

Review

Concepts

• Supervised Classification
  • The Look of Labeled Data
• Unsupervised Classification
• The Decision Tree Classifier
  • The Algorithm
  • Advantages
  • Disadvantages
  • Attributes
  • Operations

• Final Whiteboarding

Demo

Assignments

• Implement the Decision Tree Classifier
• Group Project: Estimate User Stories
• Technical Blog Post: Publish Your Post (Due Friday)
• Today I learned...