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Machine Learning

0-0-First-Words

0-1-Introduction-1

0-2-Introduction-2

0-3-Pattern-Recognition-Abstract

1-Concept-Learning-1

2-Concept-Learning-2

3-Concept-Learning-3

4-Concept-Learning-4

5-Parametric-Methods-1-MLE

6-Parametric-Methods-2-Bayesian

7-Supervised-Learning-1-Regularization-Triple-Trade-Off

8-Supervised-Learning-2-Curve-Fitting

9-Supervised-Linear-Models-1

10-Supervised-Linear-Models-2

11-Parametric-Methods-3-Regression

12-Parametric-Methods-4-Model_Selection

13-Supervised-Learning-3-VC-Dim-Pac-Learning

14-PGM-Bayesian-Decision-Network-1

15-PGM-bayesian-decision-network-2

16-PGM-Bayesian-Decision-Network-3

17-PGM-Bayesian-Decision-network-4

18-Information-Theory-Covariance-Correlation-1

19-Information-Theory-1

20-Information-Theory-2

21-Decision-Tree-1

22-Decision-Tree-2

23-ClassificationDecisionTree

24-Linear-Model-Regression

25-Bayesian-Linear-Regression

26-Bayesian-Linear-Regression-Abstract

27-Linear-Model-Classification

28-Ensemble-1-Introduction

29-Ensemble-2-Bagging-Boosting

30-Ensemble-3-Mixture-of-Expert

31-Semi-Supervised and Clustering

32-Mixture Models and EM

33-Algebra

34-Intro_Probability

37-Joint-Discrete-Mass-Density

38-Variational_Inference

Learning Theory

Scientific and Technical

Writing and Presentation

Technical English Language

Linear Control Systems

Problems and Solutions for Linear Control

Signals and Systems