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Home Teaching Summer Semester 2018 Machine Learning for Computer Vision (IN2357) (2h + 2h, 5ECTS)

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teaching:ss2018:ml4cv [2018/07/13 16:32]
Rudolph Triebel
teaching:ss2018:ml4cv [2018/10/12 17:18] (current)
Ioannis Chiotellis
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 **June, 25th**: ​ **June, 25th**: ​
 <​html><​font color="​red"><​b>​ There will be no tutorial on Thursday, June 28. </​b></​font></​html>​ <​html><​font color="​red"><​b>​ There will be no tutorial on Thursday, June 28. </​b></​font></​html>​
 +
 +**July 15th**:
 +<​html><​font color="​red"><​b>​ There will be no repeat exam in SS2018. </​b></​font></​html>​
 +
 +**July 25th**:
 +<​html><​font color="​red"><​b>​ No cheatsheets,​ calculators or other assistances are allowed in the exam. </​b></​font></​html>​
 +
  
 ==FAQ== ==FAQ==
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 13. {{teaching:​ss2018:​ml4cv:​variationalinferenceii.pdf | Variational Inference II: Expectation Propagation ​ / Sampling I}} \\ 13. {{teaching:​ss2018:​ml4cv:​variationalinferenceii.pdf | Variational Inference II: Expectation Propagation ​ / Sampling I}} \\
 14. {{teaching:​ss2018:​ml4cv:​sampling.pdf | Sampling II}} \\ 14. {{teaching:​ss2018:​ml4cv:​sampling.pdf | Sampling II}} \\
-==Exercises== 
- 
- 
-0. {{teaching:​ss2018:​ml4cv:​linalg_refresh.pdf | Linear Algebra Refresher}} 
-{{teaching:​ss2018:​ml4cv:​ex0_linalg.pdf | Linear Algebra Exercises}} 
-{{teaching:​ss2018:​ml4cv:​ex0_sol_linalg.pdf | Solutions}} 
- 
-1. {{teaching:​ss2018:​ml4cv:​ex1_probs.pdf | Probabilistic Reasoning}} 
-{{teaching:​ss2018:​ml4cv:​ex1_sol_probs.zip | Solutions Notebook}} 
- 
-2. {{teaching:​ss2018:​ml4cv:​ex2_regression.pdf | Regression}} 
-{{teaching:​ss2018:​ml4cv:​ex2_sol_regression.pdf | Solutions}} 
-{{teaching:​ss2018:​ml4cv:​polynomial_regression.zip | Code}} 
- 
-3. {{teaching:​ss2018:​ml4cv:​ex3_pgms.pdf | Graphical Models |}} 
-{{teaching:​ss2018:​ml4cv:​graph.py.zip | graph.py.zip}} 
-{{teaching:​ss2018:​ml4cv:​ex3_sol_pgms.pdf | Solutions}} 
-{{teaching:​ss2018:​ml4cv:​graph_solution.zip | graph_solution.zip}} 
- 
-4. {{teaching:​ss2018:​ml4cv:​ex4_icm.pdf | Graphical Models ||}} 
-{{teaching:​ss2018:​ml4cv:​images.zip | images.zip}} 
- 
-5. {{teaching:​ss2018:​ml4cv:​ex5_bagging_boosting.pdf | Bagging & Boosting}} 
-{{teaching:​ss2018:​ml4cv:​banknote_auth.zip | banknote_auth.zip}} 
-{{teaching:​ss2018:​ml4cv:​ex5_sol_bagging_boosting.pdf | Solutions}} 
-{{teaching:​ss2018:​ml4cv:​adaboost.zip | Code}} 
- 
-6. {{teaching:​ss2018:​ml4cv:​ex6_metric_learning.pdf | Metric Learning}} 
-{{teaching:​ss2018:​ml4cv:​ex6_sol_metric_learning.pdf | Solutions}} 
- 
-7. {{teaching:​ss2018:​ml4cv:​ex7_hmm.pdf | Hidden Markov Models}} 
-{{teaching:​ss2018:​ml4cv:​ex7_sol_hmm.pdf | Solutions }} 
-{{teaching:​ss2018:​ml4cv:​viterbi.py.zip | Code}} 
- 
-8. {{teaching:​ss2018:​ml4cv:​ex8_kernels_gps.pdf | Kernel Methods and GPs}} 
-{{teaching:​ss2018:​ml4cv:​ex8_sol_kernels_gps.pdf | Solutions}} 
- 
-9. {{teaching:​ss2018:​ml4cv:​ex9_clustering1.pdf | Clustering 1}} 
-{{teaching:​ws2016:​mlcv16:​clustering.zip | clustering.zip}} 
-{{teaching:​ss2018:​ml4cv:​ex9_sol_clustering1.pdf | Solutions}} 
-{{teaching:​ss2018:​ml4cv:​clustering_sol.zip | Code}} 
- 
-10. {{teaching:​ss2018:​ml4cv:​ex10_variational_inference.pdf | Variational Inference 1}} 
-{{teaching:​ss2018:​ml4cv:​ex10_sol_variational_inference.pdf | Solutions}} 
  
-11. {{teaching:​ss2018:​ml4cv:​ex11_sampling.pdf | Sampling}} 

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