Learning from Data

Chapter 1: Tools and Data for Machine Learning Projects

• The UCI (University of California-Irvine) ML Repository
• Introducing the Rattle package
• Using Rattle with iris

Chapter 2: Decisions, Decisions, Decisions

• Decision Tree Components
• Decision Trees in R
• Decision Trees in Rattle
• Project: A More Complex Decision Tree
• Suggested Project: Titanic

Chapter 3: Into the Forest, Randomly

• Growing a Random Forest
• Random Forests in R
• Project: Identifying Glass
• Suggested Project: Identifying Mushrooms

Chapter 4: Support Your Local Vector

• Some Data to Work With
• Separability: It’s Usually Nonlinear
• Support Vector Machines in R
• Project: House Parties

Chapter 5: K-Means Clustering

• How It Works
• K-Means Clustering in R
• Project: Glass Clusters

Chapter 6: Neural Networks

• Networks in the Nervous System
• Artificial Neural Networks
• Neural Networks in R
• Project: Banknotes
• Suggested Projects: Rattling Around

Chapter 7: Exploring Marketing

• Analyzing Retail Data
• Enter Machine Learning
• Suggested Project: Another Data Set

Chapter 8: From the City That Never Sleeps

• Examining the Data Set
• Warming Up
• Quick Suggested Project: Airline Names
• Suggested Project: Departure Delays
• Quick Suggested Project: Analyze Weekday Differences
• Suggested Project: Delay and Weather