CSCE 50603 - 001 Machine Learning

Fall 2025 Course Syllabus

JBHT Rm 0239, MoWeFr 10:45 - 11:35 AM

Schedule    Projects

 

Instructor        Dr. Lu Zhang

Office                 JBHT 522, (479)575-4382

Email                  lz006 at uark dot edu

URL                      http://csce.uark.edu/~lz006/

Office Hours MoWe 2:00 - 3:00 PM or by appointment

 

Course Material

The Elements of Statistical Learning, by Trevor Hastie, et. al. (2009). Available online: https://web.stanford.edu/~hastie/ElemStatLearn/

Machine Learning: A Probabilistic Perspective, by Kevin Murphy (2012)               

Understanding Machine Learning: From Theory to Algorithms, by Shai Shalev-Shwartz and Shai Ben-David (2014). Available online: https://www.cse.huji.ac.il/~shais/UnderstandingMachineLearning/

Dive into Deep Learning, by Aston Zhang and Zachary C. Lipton and Mu Li and Alexander J. Smola (2020). Available online: https://d2l.ai/

 

Grading

Homework 30%, mid-term 15%, group project 30%, final 25%.

 

Topic Outline

1

Introduction

Preliminaries

2

Linear regression

Decision tree

3

Bayes classifier

Instance based learning

4

Logistic regression

Perceptron

5

Support vector machine

Kernel methods

6

Neural networks

PAC learning theorem

7

Clustering

EM algorithm

8

Fair machine learning

Intro to deep learning

9

Intro to reinforcement learning

Causal modeling and inference

10

Software and packages for machine learning

Course project presentation

 

                                                                Syllabus