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  3. Lecture slides 2023/24

Lecture slides 2023/24

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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.pdf IS 01 Introduction.pdf
    • IS 02 Nature inspired computation.pdf IS 02 Nature inspired computation.pdf
    • IS 03 Predictive modeling.pdf IS 03 Predictive modeling.pdf
    • IS 04 Bias, variance and predictive models.pdf IS 04 Bias, variance and predictive models.pdf
    • IS 05 Data preprocessing.pdf IS 05 Data preprocessing.pdf
    • IS 06 Neural networks.pdf IS 06 Neural networks.pdf
    • IS 07 Natural language processing.pdf IS 07 Natural language processing.pdf
    • IS 08 Ensemble methods.pdf IS 08 Ensemble methods.pdf
    • IS 09 Kernel methods.pdf IS 09 Kernel methods.pdf
    • IS 10 Inference and explanation.pdf IS 10 Inference and explanation.pdf
    • IS 11 Reinforcement learning.pdf IS 11 Reinforcement learning.pdf
    • Joshua Evans - 1 Fundamentals of RL.pdf Joshua Evans - 1 Fundamentals of RL.pdf
    • Joshua Evans - 2 Frontiers of RL.pdf Joshua Evans - 2 Frontiers of RL.pdf
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