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CENG 5531 Machine Learning and Applications

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Syllabus

Resources:

Lectures:

Chapter 1:Introduction

Chapter 2: Bayesian Decision Theory

Chapter 3:Maximum-Likelihood and Bayesian Parameter Estimation

Chapter 4: Nonparametric Techniques

Chapter 5: Linear Discriminant Functions

Chapter 10: Unsupervised Learning and Clustering

 

Review Questions for the Final Exam

 

Homework

HW1 HW2 HW3

 HW4 HW5 HW6

HW7 HW8

HW9 HW10