Study Guide
User Manual:
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Page Count: 41
- Linear Algebra and Calculus
- Convex Optimization
- Probability and Statistics
- Information Theory
- Learning Theory
- Linear Regression
- Logistic Regression
- Softmax Regression
- Generalized Linear Models
- Perceptron
- Support Vector Machines
- Margin Classification
- Generative Learning: Gaussian Discriminant Analysis
- Generative Learning: Naive Bayes
- Tree-based Methods
- K-Nearest Neighbors
- K-Means Clustering
- Expectation-Maximization
- Principal Component Analysis
- Independent Component Analysis
- Reinforcement Learning
- Probabilistic Graphical Models
- Deep Learning: Basics
- Deep Learning: Advanced