Deep Learning - 課程網站

Deep Learning - Youtube

00 - Notation

02 - Linear Algebra

• Span & Linear Dependence
• Norm
• Eigendecomposition (Spectral decomposition)
• Singularity & Positive Definiteness
• SVD & Pseudoinverse
• Trace & Determinant

03 - Prob and Info Theories

• Random Variables & Probability Distribution
• Multivariate & Derived Variables
• Bayes Rules & Statistics
• PCA
• Technical Details of Random Variables
• Common Probability Distributions
• Common Parametrizing Functions
• Information Theory
• KL Divergence
• Decision Trees & Random Forests

04 - Numerical Optimization

• Numerical Computation
• Optimization Problems
• Gradient Descent
• Newton's Method
• Optimization in ML
• Constrained Optimization
• Linear & Polynomial Regression
• Generalizability & Regularization
• Duality

05 - Learning Theory & Regularization

• Learning Theory
• Point Estimation: Bias & Variance
• Decomposing Generalization Error
• Regularization

06 - Probabilistic Models

• Probabilistic Models
• Linear Regression
• Logistic Regression
• MAP Estimation
• Bayesian Estimation