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teaching:ws2016:mlcv16 [2017/02/10 12:02] chiotell |
teaching:ws2016:mlcv16 [2017/04/12 11:02] (current) chiotell |
0. {{teaching:ws2016:mlcv16:linalg_refresh.pdf | Linear Algebra Refresher}} | 0. {{teaching:ws2016:mlcv16:linalg_refresh.pdf | Linear Algebra Refresher}} |
{{teaching:ws2016:mlcv16:ex0_linalg.pdf | Linear Algebra Exercises}} | {{teaching:ws2016:mlcv16:ex0_linalg.pdf | Linear Algebra Exercises}} |
{{teaching:ws2016:mlcv16:ex0_sol_linalg.pdf | Solution 0}} | |
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1. {{teaching:ws2016:mlcv16:ex1_probs.pdf | Probabilistic Reasoning}} | 1. {{teaching:ws2016:mlcv16:ex1_probs.pdf | Probabilistic Reasoning}} |
{{teaching:ws2016:mlcv16:ex1_sol_probs.zip | Solution 1}} | |
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2. {{teaching:ws2016:mlcv16:ex2_regression_kernels_gps.pdf | Regression, Kernels, GPs}} {{teaching:ws2016:mlcv16:train_data.txt | train_data.txt}} | 2. {{teaching:ws2016:mlcv16:ex2_regression_kernels_gps.pdf | Regression, Kernels, GPs}} {{teaching:ws2016:mlcv16:train_data.txt | train_data.txt}} |
{{teaching:ws2016:mlcv16:ex2_sol_regress_kernels.zip | Solution 2}} | |
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3. {{teaching:ws2016:mlcv16:ex3_gmm_em.pdf | K-Means, EM, GMM}} {{teaching:ws2016:mlcv16:clustering.zip | clustering.zip}} | 3. {{teaching:ws2016:mlcv16:ex3_gmm_em.pdf | K-Means, EM, GMM}} {{teaching:ws2016:mlcv16:clustering.zip | clustering.zip}} |
{{teaching:ws2016:mlcv16:ex3_sol_gmm_em.pdf | Solution 3}} {{:teaching:ws2016:mlcv16:kmeans_gmm_em.zip|}} | |
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4. {{teaching:ws2016:mlcv16:ex4_deepnets_boosting.pdf | Deep Learning, Boosting}} {{:teaching:ws2015:mlcv15:banknote_auth.zip| banknote_auth.zip}} | 4. {{teaching:ws2016:mlcv16:ex4_deepnets_boosting.pdf | Deep Learning, Boosting}} {{:teaching:ws2015:mlcv15:banknote_auth.zip| banknote_auth.zip}} |
{{:teaching:ws2016:mlcv16:ex4_sol_deepnets_boosting.pdf| Solution 4}} | |
{{:teaching:ws2016:mlcv16:adaboost.zip|}} | |
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5. {{:teaching:ws2016:mlcv16:ex5_pgm_hmm.pdf| Graphical Models, HMM}} | 5. {{:teaching:ws2016:mlcv16:ex5_pgm_hmm.pdf| Graphical Models, HMM}} |
{{:teaching:ws2016:mlcv16:ex5_sol_pgm_hmm.pdf| Solution 5}} | |
{{:teaching:ws2016:mlcv16:viterbi.py.zip|}} | |
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6. {{:teaching:ws2016:mlcv16:ex6_sampling.pdf| Sampling and Variational Inference}} | 6. {{:teaching:ws2016:mlcv16:ex6_sampling.pdf| Sampling and Variational Inference}} |
{{:teaching:ws2016:mlcv16:ex6_sol_sampling.pdf| Solution 6}} | |
{{:teaching:ws2016:mlcv16:particle_filter.zip|}} | |
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