Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Graduate School of Sciences
  • Department of Industrial Engineering
  • Master of Arts (MA) Degree
  • Course Structure Diagram with Credits
  • Optimization for Machine Learning
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title ENM529 - Optimization for Machine Learning
Course Type Elective Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOKTOR ÖĞRETİM ÜYESİ GÜLÇİN DİNÇ YALÇIN
Mode of Delivery in person
Prerequisites -
Courses Recomended -
Recommended Reading List -
Assessment methods and criteria midterm exam, project, final exam
Work Placement -
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Optimization, machine learning and convexity
Week - 2 Convex optimization for machine learning
Week - 3 General formulation of machine learning problems and machine learning problem: Support Vector Machines
Week - 4 Machine learning problem: Support Vector Machines
Week - 5 Machine learning problem: Logistic Regression
Week - 6 Gradient decent method
Week - 7 Line search in gradient descent method
Week - 8 Stochastic gradient descent method
Week - 9 Noise reduction methods
Week - 10 Adaptive methods
Week - 11 Convergence analysis of first-order methods
Week - 12 Second-order methods
Week - 13 Stochastic BFGS and L-BFGS methods
Week - 14 Convergence analysis of second-order methods

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Competences
  • Questoning
  • Problem solving
  • Elementary computing skills

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 30
Homework 1 30
Final Exam 1 40
Toplam (%) 100
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