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Home Teaching Summer Semester 2016 Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)

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teaching:ss2016:mlcv16 [2016/07/29 16:46]
Rudolph Triebel
teaching:ss2016:mlcv16 [2016/09/02 12:08] (current)
Ioannis Chiotellis
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 0. {{teaching:​ss2016:​mlcv16:​linalg_refresh.pdf | Linear Algebra Refresher}}\\ 0. {{teaching:​ss2016:​mlcv16:​linalg_refresh.pdf | Linear Algebra Refresher}}\\
-1. {{teaching:​ss2016:​mlcv16:​ex1_linalg_probs.pdf | Linear Algebra and Probabilistic Reasoning}} |  +1. {{teaching:​ss2016:​mlcv16:​ex1_linalg_probs.pdf | Linear Algebra and Probabilistic Reasoning}} ​
-{{teaching:​ss2016:​mlcv16:​ex1_sol_linalg_probs.pdf | Solution 1}}+
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-2. {{teaching:​ss2016:​mlcv16:​ex2_regression_pgms.pdf | Regression and Probabilistic Graphical Models}} |  +2. {{teaching:​ss2016:​mlcv16:​ex2_regression_pgms.pdf | Regression and Probabilistic Graphical Models}} ​
-{{teaching:​ss2016:​mlcv16:​ex2_sol_regression_pgms.pdf | Solution 2}}+
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-3. {{teaching:​ss2016:​mlcv16:​ex3_deep_nets_hmm.pdf | Neural Networks and Hidden Markov Models}} | +3. {{teaching:​ss2016:​mlcv16:​ex3_deep_nets_hmm.pdf | Neural Networks and Hidden Markov Models}} ​
-{{teaching:​ss2016:​mlcv16:​ex3_sol_deepnets_hmm.pdf | Solution 3}} +
-{{teaching:​ss2016:​mlcv16:​viterbi_code.zip | viterbi_code}}+
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 4. {{teaching:​ss2016:​mlcv16:​ex4_boosting_em.pdf | Boosting and Expectation-Maximization}} 4. {{teaching:​ss2016:​mlcv16:​ex4_boosting_em.pdf | Boosting and Expectation-Maximization}}
 {{teaching:​ss2016:​mlcv16:​banknote_auth.zip | banknote_auth.zip}} {{teaching:​ss2016:​mlcv16:​banknote_auth.zip | banknote_auth.zip}}
-{{teaching:​ss2016:​mlcv16:​fisher-iris.zip | fisher-iris.zip}} |  +{{teaching:​ss2016:​mlcv16:​fisher-iris.zip | fisher-iris.zip}} ​
-{{teaching:​ss2016:​mlcv16:​ex4_sol_boosting_em.pdf | Solution 4}} +
-{{teaching:​ss2016:​mlcv16:​ex4_code_sol.zip | code.zip}}+
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-5. {{teaching:​ss2016:​mlcv16:​ex5_kernels_gps.pdf | Kernel methods - Gaussian Processes}} | +5. {{teaching:​ss2016:​mlcv16:​ex5_kernels_gps.pdf | Kernel methods - Gaussian Processes}} ​
-{{teaching:​ss2016:​mlcv16:​ex5_sol_kernels_gps.pdf | Solution 5}} +
-{{teaching:​ss2016:​mlcv16:​gp_classification.zip | gp_code.zip}}+
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-6. {{teaching:​ss2016:​mlcv16:​ex6_sampling.pdf | Sampling methods and Variational Inference}} |  +6. {{teaching:​ss2016:​mlcv16:​ex6_sampling.pdf | Sampling methods and Variational Inference}} ​
-{{teaching:​ss2016:​mlcv16:​ex6_sol_sampling.pdf | Solution 6}} +
-{{teaching:​ss2016:​mlcv16:​particle_filter.zip | particle_filter.zip}}+
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