Data Science & ML track

Random Forest

Bagging, feature randomness, out-of-bag estimates and feature importance.

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1

Random Forest Overview

Concept · Hands-on lab included

2

Bagging and the Bootstrap

Concept · Hands-on lab included

3

Random Feature Subsets

Concept · Hands-on lab included

4

Out-of-Bag Score and Honest Validation

Concept · Hands-on lab included

5

Feature Importance and Stability

Concept · Hands-on lab included

6

Tuning Random Forests

Concept · Hands-on lab included

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