Machine Learning – Spring 2020

Course No: 0907751
Course Name: Special Topics in Computer Engineering (Machine Learning)

Facebook group: https://www.facebook.com/groups/315669882258644/

Handouts:
Course Syllabus (pdf)
Slides:

  • 1. Course Introduction (pptx)
  • 2. Machine Learning Introduction (pdf)
  • 3. Information about the term project (pdf)
  • 4. Python Introduction (pdf)
  • 5. Python Basics (pdf)
  • 6. Important Python Packages (pdf)
  • 7. End-to-End Machine Learning Project (pdf)
  • 8. Classification (pdf)
  • 9. Training Models (pdf)
  • 10. Classical Techniques (pdf)
  • 11. Neural Networks (pdf)
  • 12. Artificial Neural Networks with Keras (pdf)
  • 13. Deep Neural Networks (pdf)
  • 14. Deep Computer Vision Using Convolutional Neural Networks (pdf)
  • 15. Recurrent Neural Networks (pdf)
  • 16. Reinforcement Learning (pdf)
  • 17. Recommender Systems (pdf)

Videos:

  • Python
  • Python Introduction (YouTube) by M. Abdel-Majeed
  • Python Basics (YouTube: Part 1, Part 2, Part 3) by G. Abandah
  • Important Python Packages (YouTube) by M. Abdel-Majeed
  • Training Models (YouTube)
  • Classical Techniques 1: k-nearest neighbors (YouTube)
  • Classical Techniques 2: Support Vector Machines (YouTube)
  • Classical Techniques 3: Decision Trees (YouTube)
  • Classical Techniques 4: Ensemble Learning and Random Forests (YouTube)
  • Neural Networks (YouTube)
  • Artificial Neural Networks with Keras (YouTube: Part 1, Part 2, Part 3)
  • 13. Deep Neural Networks (YouTube: Part 1, Part 2, Part 3)
  • 14. Deep Computer Vision Using Convolutional Neural Networks (YouTube: Part 1, Part 2, Part 3)
  • 15. Recurrent Neural Networks (YouTube)
  • 16. Reinforcement Learning (YouTube: Part 1, Part 2)
  • 17. Recommender Systems (YouTube)

Solutions:

  • Midterm exam (Cancelled due to COVID-19), Final Exam (pdf)

Grades: Project and final exam marks (pdf)

Last update on 3/6/2020