Machine Learning

Large Margin Intuition

Support Vector Machine

Trading Off Precision and Recall

Error Metrics for Skewed Classes

Error Analysis

Prioritizing What to Work On

Deciding what to try next (revisited)

Learning Curves

Diagnosing Regularization Bias vs. Variance

Model Selection and Train/Validation/Test Sets

Evaluating Hypothesis

Random Initialization

Gradient Checking

Unrolling Parameters

Backpropagation Algorithm 2