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Course Code and Name
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EEE 450- Introduction to Machine Learning
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Term
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Fall 2018-2019
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Instructor
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Associate Professor Aytuğ ONAN
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E-mail
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aytug.onan@cbu.edu.tr
aytugonan@gmail.com
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Course Day and Time
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Thursday, 13.30-16.00
Office Hour: Wednesday,
10.30-12.00.
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Course Website
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http://aytugonan.cbu.edu.tr/EEE450_index.html
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Objectives
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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.
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Tentative Course Outline
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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!
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Textbook
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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.
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Supplementary Materials
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Kuncheva, L. I. (2004). Combining pattern
classifiers: methods and algorithms. John Wiley & Sons.
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Evaluation
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