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courses:be5b33kui:lectures:start [2017/05/11 12:23]
hoffmmat
courses:be5b33kui:lectures:start [2018/01/16 09:50]
svobodat
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PDF of the slides will be posted on this page. Note, however, that lectures will contain a significant portion of blackboard writing as well as some live programming pieces. Reading/watching slides only is not enough. Active participation in lectures is welcomed and encouraged.
PDF of the slides will be posted on this page. Note, however, that lectures will contain a significant portion of blackboard writing as well as some live programming pieces. Reading/watching slides only is not enough. Active participation in lectures is welcomed and encouraged.
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^ datum ^ č.t. ^ S/L ^ náplň ^
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| 19.02.2018 | 1. | S | |
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| 26.03.2018 | 6. | L | |
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| 02.04.2018 | 7. | S | Svátek |
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| 09.04.2018 | 8. | L | |
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| 16.04.2018 | 9. | S | |
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| 23.04.2018 | 10. | L | |
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| 30.04.2018 | 11. | S | |
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| 07.05.2018 | 12. | L | |
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^ date ^ week ^ topic ^
^ date ^ week ^ topic ^
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| 24.04.2017 | 10. | Reinforcement learning. What if nothing is known about the probability of action outcomes and we have to learn from final success or failure? {{:courses:be5b33kui:lectures:kui-08-rl.pdf|}} |
| 24.04.2017 | 10. | Reinforcement learning. What if nothing is known about the probability of action outcomes and we have to learn from final success or failure? {{:courses:be5b33kui:lectures:kui-08-rl.pdf|}} |
| <del>01.05.2017</del> | 11. ^ Public holiday |
| <del>01.05.2017</del> | 11. ^ Public holiday |
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| **02.05.2017** | 11. | Bayesian classification and decisions - [[https://sites.google.com/site/matejhof/home|Matej Hoffmann]] . How to decide optimally if we know all the (conditional) probabilities. {{:courses:be5b33kui:lectures:kui-11-bayes.pdf|}} |
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| **02.05.2017** | 11. | Bayesian classification and decisions - [[https://sites.google.com/site/matejhof/home|Matej Hoffmann]]. How to decide optimally if we know all the (conditional) probabilities. {{:courses:be5b33kui:lectures:kui-11-bayes.pdf|}} |
| <del>08.05.2017</del> | 12. ^ Public holiday |
| <del>08.05.2017</del> | 12. ^ Public holiday |
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| **11.05.2017** | 12. | Classification
– Perceptron, k
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nn and relationship to Bayesian classifier -
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| **11.05.2017** | 12. | Classification - [[https://sites.google.com/site/matejhof/home|Matej Hoffmann]]
. Perceptron, k-nn and relationship to Bayesian classifier -
{{:courses:be5b33kui:lectures:kui-12-classification.pdf|}} |
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[[https://sites.google.com/site/matejhof/home|Matej Hoffmann]]
{{:courses:be5b33kui:lectures:kui-12-classification.pdf|}} |
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| 15.05.2017 | 13. | Learning probabilistic models - [[https://sites.google.com/site/matejhof/home|Matej Hoffmann]]
. Slides from Jiri Matas: {{:courses:be5b33kui:lectures:Matas_pr_03_parameter_estimation_2016_10_17.pdf|}} - up to slide 15.
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| 15.05.2017 | 13. | Learning probabilistic models - [[https://sites.google.com/site/matejhof/home|Matej Hoffmann]] |
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| 22.05.2017 | 14. |
Solving problems on paper/blackboard - fully interactive lecture; preparing for the exam a bit
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| 22.05.2017 | 14. |
ToBeDecided
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courses/be5b33kui/lectures/start.txt
· Last modified: 2018/02/18 15:41 by
svobodat