EEE 450--- Introduction to Machine Learning

Izmir Katip Çelebi University, Faculty of Engineering and Architecture

Fall 2019


Course Code and Name

EEE 450- Introduction to Machine Learning


Fall 2018-2019


Associate Professor Aytuğ ONAN


Course Day and Time

Thursday, 13.30-16.00

Office Hour: Wednesday, 10.30-12.00.

Course Website


In the modern IT world, businesses often have access to large amounts of data collected from customer management systems, web services, customer interaction, etc. The data in itself does not bring value to the business; we must bring meaning to the data to create value. Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data. This course will focus on applied machine learning, where we learn what algorithms and approaches to apply on different types of data.

Tentative Course Outline


Week#1: Course Introduction

Week#2: Introduction to Artificial Intelligence, Data and Learning

Week#3: Text Classification

Week#4: Numerical Regression

Week#5: Decision Support, Kernel Methods and Support Vector Machines

Week#6: Artificial Neural Networks

Week#7: Midterm Review!

Week#8: Midterm Week

Week#9: Deep Learning

Week#10: Ensemble Learning

Week#11: Genetic Algorithms

Week#12: Student Presentations

Week#13: Student Presentations

Week#14: Final Review!


Mining of Massive Datasets
Leskovec, Jure & Rajaraman, Anand & Ullman, Jeffrey David (2014), Cambridge University Press, 476 pages.
Available for free online here.

Deep Learning
Goodfellow, Ian & Bengio, Yoshua & Courville, Aaron (2016), MIT Press, 781 pages.
Available for free online here.

Supplementary Materials

Kuncheva, L. I. (2004). Combining pattern classifiers: methods and algorithms. John Wiley & Sons.


  • Homework Assignments: 20%

  • Midterm Exam: 20%

  • Term Project: 20%

  • Final Exam: 40%