1

Introduction to Course(PDF - 1.2 MB)

LOM

2

Decision Analysis 1 (PDF)

LOM

3

Decision Analysis 2, Linear Regression (PDF)

LOM

4

Predictive Modeling, Data Collection

SV

5

Logistic Regression, MLE (PDF)

LOM

6

Evaluation (PDF)

LOM

7

Instance-based Models 1 - kNN

SV

8

Instance-based Models 2 - Trees and Rules

SV

9

Homework 2 - Trees and Rules

SV

10

Ensemble Models (PDF)

LOM

11

PCA, LDA (PDF)

LOM

12

Unsupervised Learning (PDF)

LOM

13

Neural Networks (PDF - 1.2 MB)

LOM

14

Homework 2 - Trees and Rules

SV

15

Review (PDF)

LOM

16

Survival Analysis (PDF)

LOM

Midterm

SV

17

Statistical Learning Theory (PDF)

SV

18

Model Construction Schemas 1 (PDF)

SV

19

Model Construction Schemas 2

SV

20

Preprocessing Algorithms 1

SV

21

Preprocessing Algorithms 2

SV

22

Analysis of Problems, Complexity (PDF)

SV

23

Search Algorithms

SV

24

Bioinformatics 1 (Hypothesis Generation, Sequence Alignment) (PDF 1) (PDF 2) experiment.r (R)

SV

25

Bioinformatics 2 (Phylogenetic Trees, Haplotype Tagging)

SV

26

Student Project Presentation 1

SV

27

Student Project Presentation 2

SV