Weekly outline

  • General

    • About the course                                                                                                                                            

    • Lectures                                                                                                                                                 

    • The course syllabus.

      Topic
      		 Lectures
      1
      		 Syllabus and obligations
      2 Nature inspired computation, genetic algorithms
      3
      		 Predictive modeling
      4 Bias and variance
      5
      		 Feature evaluation and selection
      6
      		 Ensemble learning
      7
      		 Kernel methods
      8
      		 Neural networks
       9 Natural language processing
      10
      		 Model explanation methods
      11
      		 Reinforcement learning


    • Exams                                                                                                                                                    

    • A sample of oral exam questions File Uploaded 15/01/21, 21:24

    • Lab work (general)                                                                                                                           

    • Lab work (assignment 1)                                                                                                                  

    • Lab work (assignment 2)                                                                                                                

    • Lab work (Assignment 3)                                                                                                             

    • Theoretical seminars File Uploaded 28/12/21, 10:48
    • Dataset sentiment File Uploaded 15/03/22, 14:50

    • Additional material                                                                                                                        

    • Quizzes                                                                                                                                            

  • 4. Oktober - 8. Oktober


    • Practical sessions start the 2nd week of the semester.

  • 11. Oktober - 15. Oktober


  • 18. Oktober - 22. Oktober


    • Labs:

      Genetic algorithms
      - Data visualization

  • 25. Oktober - 29. Oktober


    • 1. November - 5. November


      • 8. November - 12. November


        • LABS:

          - Classification


      • 15. November - 19. November


        • 22. November - 26. November


          • LABS:

            - Ensemble methods

        • 29. November - 3. December


          • LABS:
            Ensemble models

        • 6. December - 10. December


          • 13. December - 17. December

             

            • LABS: Neural Networks


              Instructions:

              This lab is Python-based, and requires rather heavy computing resources. The most elegant way to successful execution of the notebook is by using it within the Colab environment: https://colab.research.google.com/

              Simply download the ipynb file provided below and load it within Colab: File -> open notebook -> Upload (rightmost option), and you are good to go!


          • 20. December - 24. December


            • 27. December - 31. December

               We wish you a Merry Christmas and a Happy New Year!


              • 3. Januar - 7. Januar