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All Programs
Computers
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Learning from Data
Learning from Data
Curriculum
8 Sections
33 Lessons
10 Weeks
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Chapter 1: Tools and Data for Machine Learning Projects
3
1.1
The UCI (University of California-Irvine) ML Repository
1.2
Introducing the Rattle package
1.3
Using Rattle with iris
Chapter 2: Decisions, Decisions, Decisions
5
2.1
Decision Tree Components
2.2
Decision Trees in R
2.3
Decision Trees in Rattle
2.4
Project: A More Complex Decision Tree
2.5
Suggested Project: Titanic
Chapter 3: Into the Forest, Randomly
4
3.1
Growing a Random Forest
3.2
Random Forests in R
3.3
Project: Identifying Glass
3.4
Suggested Project: Identifying Mushrooms
Chapter 4: Support Your Local Vector
4
4.1
Some Data to Work With
4.2
Separability: It’s Usually Nonlinear
4.3
Support Vector Machines in R
4.4
Project: House Parties
Chapter 5: K-Means Clustering
3
5.1
How It Works
5.2
K-Means Clustering in R
5.3
Project: Glass Clusters
Chapter 6: Neural Networks
5
6.1
Networks in the Nervous System
6.2
Artificial Neural Networks
6.3
Neural Networks in R
6.4
Project: Banknotes
6.5
Suggested Projects: Rattling Around
Chapter 7: Exploring Marketing
3
7.1
Analyzing Retail Data
7.2
Enter Machine Learning
7.3
Suggested Project: Another Data Set
Chapter 8: From the City That Never Sleeps
6
8.1
Examining the Data Set
8.2
Warming Up
8.3
Quick Suggested Project: Airline Names
8.4
Suggested Project: Departure Delays
8.5
Quick Suggested Project: Analyze Weekday Differences
8.6
Suggested Project: Delay and Weather
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