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TU Machine Learning
Folder: Notes-📝/TU-Machine-Learning
54 items under this folder.
Nov 24, 2025
HW
Nov 24, 2025
ADALINE
Nov 24, 2025
Ada Boost
Nov 24, 2025
Basic Bayesian Statistics
Nov 24, 2025
Bayesian Decision Theory Framework with Costs
Nov 24, 2025
Bayesian Decision with Gaussian Distribution
Nov 24, 2025
Bayesian Estimation
Nov 24, 2025
Bayesian Rule Forms
Nov 24, 2025
Branch-Bound Algorithm
Nov 24, 2025
Classification
Nov 24, 2025
Commonly Used Kernels
Nov 24, 2025
Condensed Nearest Neighbor Method
Nov 24, 2025
Decision Trees
Nov 24, 2025
Distances for NN Methods
Nov 24, 2025
Editing Nearest Neighbor Method
Nov 24, 2025
Ensemble Learning
Nov 24, 2025
Feature Extraction
Nov 24, 2025
Fisher Criterion
Nov 24, 2025
Generalized Optimal Hyperplane
Nov 24, 2025
Information Gain
Nov 24, 2025
Invertible Matrices
Nov 24, 2025
K-Nearest Neighbor Method
Nov 24, 2025
Karhunen-Loeve Transform
Nov 24, 2025
Kernel Trick
Nov 24, 2025
Kuhn Tucker theorem
Nov 24, 2025
Linear Discriminant Analysis
Nov 24, 2025
Linear Regression
Nov 24, 2025
Linearly Separable
Nov 24, 2025
Logistic Regression
Nov 24, 2025
Markov Chain
Nov 24, 2025
Maximum Likelihood Estimation
Nov 24, 2025
Mercer Theorem
Nov 24, 2025
Minimum Squared Error
Nov 24, 2025
Multi-Layer Perceptron
Nov 24, 2025
Multi-class Logistic Regression
Nov 24, 2025
Naive Bayes Classifier
Nov 24, 2025
Nearest-Neighbor Method
Nov 24, 2025
Neyman-Pearson Criterion
Nov 24, 2025
Normalized Augmented Feature Vector
Nov 24, 2025
Optimal Hyperplane
Nov 24, 2025
Perceptron
Nov 24, 2025
Principal Component Analysis
Nov 24, 2025
Pruning in Decision Trees
Nov 24, 2025
R2 Goodness of Fit
Nov 24, 2025
Random Forest
Nov 24, 2025
Regression Trees
Nov 24, 2025
Separability of Classes
Nov 24, 2025
Shannon Entropy
Nov 24, 2025
Standard Results of Matrix Calculus
Nov 24, 2025
Statistical Learning Theory
Nov 24, 2025
Statistical Significance of Regression Coefficient
Nov 24, 2025
TU ML Summary
Nov 24, 2025
Usage of SVMs
Nov 24, 2025
t-SNE