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Učilnica FRI 23/24
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  1. IntSys
  2. Lecture slides 2023/24

Lecture slides 2023/24

Warning: The slides from the lectures are outlines of the topics covered. Do not consider them as a replacement for the literature.
    • IS 01 Introduction.pdfIS 01 Introduction.pdf
    • IS 02 Nature inspired computation.pdfIS 02 Nature inspired computation.pdf
    • IS 03 Predictive modeling.pdfIS 03 Predictive modeling.pdf
    • IS 04 Bias, variance and predictive models.pdfIS 04 Bias, variance and predictive models.pdf
    • IS 05 Data preprocessing.pdfIS 05 Data preprocessing.pdf
    • IS 06 Neural networks.pdfIS 06 Neural networks.pdf
    • IS 07 Natural language processing.pdfIS 07 Natural language processing.pdf
    • IS 08 Ensemble methods.pdfIS 08 Ensemble methods.pdf
    • IS 09 Kernel methods.pdfIS 09 Kernel methods.pdf
    • IS 10 Inference and explanation.pdfIS 10 Inference and explanation.pdf
    • IS 11 Reinforcement learning.pdfIS 11 Reinforcement learning.pdf
    • Joshua Evans - 1 Fundamentals of RL.pdfJoshua Evans - 1 Fundamentals of RL.pdf
    • Joshua Evans - 2 Frontiers of RL.pdfJoshua Evans - 2 Frontiers of RL.pdf
◄ Course description and students obligations 2023/24
Some recordings of the partially outdated lectures are available in MS Teams, UL FRI Intelligent systems team, use the code 6zwq5bg for access. ►
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