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teaching:ws2018:ml4cv [2019/02/07 20:07] chiotell |
teaching:ws2018:ml4cv [2019/10/23 16:54] chiotell |
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==Prerequisites== | ==Prerequisites== |
Linear Algebra, Calculus and Probability Theory are essential builex3_pgms.pdfding blocks to this course. The homework exercises do not have to be handed in. Solutions for the programming exercises will be provided in ** Python **. | Linear Algebra, Calculus and Probability Theory are essential building blocks to this course. The homework exercises do not have to be handed in. Solutions for the programming exercises will be provided in ** Python **. |
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14. {{teaching:ws2018:ml4cv:sampling.pdf | Sampling}} \\ | 14. {{teaching:ws2018:ml4cv:sampling.pdf | Sampling}} \\ |
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==Exercises== | |
0. {{teaching:ws2018:ml4cv:ex0_linalg.pdf | Linear Algebra}} | |
{{teaching:ws2018:ml4cv:ex0_sol_linalg.pdf | Solutions}} | |
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1. {{teaching:ws2018:ml4cv:ex1_probs.pdf | Probabilistic Reasoning}} {{teaching:ws2018:ml4cv:ex1_sol_probs.zip | Solutions}} | |
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2. {{teaching:ws2018:ml4cv:ex2_regression.pdf | Regression}} | |
{{teaching:ws2018:ml4cv:ex2_sol_regression.pdf | Solutions}} | |
{{teaching:ws2018:ml4cv:polynomial_regression.zip | Code}} | |
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3. {{teaching:ws2018:ml4cv:ex3_pgms.pdf | Graphical Models}} | |
{{teaching:ws2018:ml4cv:graph.py.zip | graph.py}} | |
{{teaching:ws2018:ml4cv:ex3_sol_pgms.pdf | Solutions}} | |
{{teaching:ws2018:ml4cv:graph_solution.zip | Code}} | |
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4. {{teaching:ws2018:ml4cv:ex4_bagging_boosting.pdf | Bagging and Boosting}} | |
{{teaching:ws2018:ml4cv:banknote_auth.zip | banknote_auth.zip}} | |
{{teaching:ws2018:ml4cv:ex4_sol_bagging_boosting.pdf | Solutions}} | |
{{teaching:ws2018:ml4cv:adaboost.zip | Code}} | |
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5. {{teaching:ws2018:ml4cv:ex5_metric_learning.pdf | Metric Learning}} | |
{{teaching:ws2018:ml4cv:ex5_sol_metric_learning.pdf | Solutions}} | |
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6. {{teaching:ws2018:ml4cv:ex6_kernels_gps.pdf | Kernels and Gaussian Processes}} | |
{{teaching:ws2018:ml4cv:ex7_sol_kernels_gps.pdf | Solutions}} | |
{{teaching:ws2018:ml4cv:gp_regression.zip | Code}} | |
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7. {{teaching:ws2018:ml4cv:ex7_deeplearning.pdf | Deep Learning}} | |
{{teaching:ws2018:ml4cv:ex7_sol_deepnets.pdf | Solutions}} | |
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8. {{teaching:ws2018:ml4cv:ex8_clustering1.pdf | Clustering}} | |
{{teaching:ws2018:ml4cv:ex8_sol_clustering.pdf | Solutions}} | |
{{teaching:ws2018:ml4cv:clustering_sol.zip | Code}} | |
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9. {{teaching:ws2018:ml4cv:ex9_vi.pdf | Variational Inference |}} | |
{{teaching:ws2018:ml4cv:ex9_sol_vi1.pdf | Solutions}} | |
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10. {{teaching:ws2018:ml4cv:ex10_vi2.pdf | Variational Inference ||}} | |
{{teaching:ws2018:ml4cv:ex10_sol_vi2.pdf | Solutions}} | |
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11. {{teaching:ws2018:ml4cv:ex11_sampling.pdf | Sampling}} | |
{{teaching:ws2018:ml4cv:ex11_sol_sampling.pdf | Solutions}} | |
{{teaching:ws2018:ml4cv:particle_filter.zip | Code}} | |
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