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| || '''Room:''' || FR 1505 (Mondays) und FR 6043 (Wednesday) || | || '''Room:''' || FR 6046 (Mondays) und FR 6043 (Wednesdays) || |
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| * [[attachment:ML_Praktikum_U01_en.pdf|Problem sheet #1 (Matlab)]], tests: [[attachment:U01_test_distmat.m|U01_test_distmat.m]],[[attachment:U01_test_mydet.m|U01_test_mydet.m]], '''link to PASSR will appear soon''' | * [[attachment:ML_Praktikum_U01_en.pdf|Problem sheet #1 (Matlab)]], tests: [[attachment:U01_test_distmat.m|U01_test_distmat.m]],[[attachment:U01_test_mydet.m|U01_test_mydet.m]], [[https://ml01.zrz.tu-berlin.de/~paul/pass.pl?conf=ss11_prak01.conf|PASS]] |
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| * [[attachment:ML_Praktikum_U02_en.pdf|Problem sheet #2 (unsupervised learning)]], Data: [[attachment:fishbowl.mat|fishbowl.mat]], [[attachment:flatroll.mat|flatroll.mat]], [[attachment:swissroll.mat|swissroll.mat]], [[attachment:U01_usps.mat|U01_usps.mat]]. [[attachment:lle_talk.pdf|LLE slides]]. Tests: [[attachment:U02_tests.zip|U02_tests.zip]]. '''link to PASSR will appear soon''' | * [[attachment:ML_Praktikum_U02_en.pdf|Problem sheet #2 (unsupervised learning)]], Data: [[attachment:flatroll.mat|flatroll.mat]], [[attachment:fishbowl_swissroll_correct.mat|fishbowl_swissroll_correct.mat]], [[attachment:U01_usps.mat|U01_usps.mat]]. [[attachment:lle_talk.pdf|LLE slides]]. Tests: [[attachment:U02_tests.zip|U02_tests.zip]], [[https://ml01.zrz.tu-berlin.de/~paul/pass.pl?conf=ss11_prak02.conf|PASS]] |
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| * [[attachment:ML_Praktikum_U03.pdf|Problem sheet #3 (Clustering, EM)]], '''english version coming soon''' | * [[attachment:ML_Praktikum_U03.pdf|Problem sheet #3 (Clustering, EM)]], [[attachment:ML_Praktikum_U03_en.pdf|English version]], Data: [[attachment:U03_5gaussians.dat|U03_5gaussians.dat]], [[attachment:U03_2gaussians.dat|U03_2gaussians.dat]], [[https://ml01.zrz.tu-berlin.de/~paul/pass.pl?conf=ss11_prak03.conf|PASS]], Tests: [[attachment:U03_tests.zip|U03_tests.zip]] * [[attachment:ML_Praktikum_U04.pdf|Problem sheet #4 (Classification: KRR, CV, ROC)]], [[attachment:ML_Praktikum_U04_en.pdf|English version]], [[https://ml01.zrz.tu-berlin.de/~paul/pass.pl?conf=ss11_prak04.conf|PASS]], Tests: [[attachment:U04_test_CV_krr.m|U04_test_CV_krr.m]], [[attachment:U04_datasets.tar.gz|Datasets]] * [[attachment:ML_Praktikum_U05_en.pdf|Problem sheet #5 (SVMs)]], [[attachment:U05_datasets.zip|Datasets]], [[https://ml01.zrz.tu-berlin.de/~paul/pass.pl?conf=ss11_prak05.conf|PASS]] |
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| || '''Matrikelnr.''' || '''Blatt 1''' || '''Blatt 2''' || '''Blatt 3''' || '''Blatt 4''' || '''Blatt 5''' || | || '''Matrikelnr.''' || '''Sheet 1''' || '''Sheet 2''' || '''Sheet 3''' || '''Sheet 4''' || '''Sheet 5''' || ||305493||5||20||15||19||20|| ||307336||5||20||18||18||20|| ||306383||5||20||18||18||20|| ||331086||5||22||20||18||20|| ||310234||5||22||20||18||20|| ||310260||5||17||19||20||15|| ||311217||5||17||19||20||15|| ||315728||5||18||20||20||20|| ||314519||5||18||20||20||20|| ||327898||5||20||20||15||18|| ||329282||5||20||20||15||18|| ||329499||5||20||20||20||20|| ||329478||5||20||20||20||20|| ||334450||5||21||21||15||20|| ||335614||5||21||20||19||15|| ||336016||5||21||20||19||15|| |
Praktikum Maschinelles Lernen und Datenanalyse
Schedule:
Irregular, see calendar
Room:
FR 6046 (Mondays) und FR 6043 (Wednesdays)
Lecturer
Prof. Dr. Klaus-Robert Müller
Contact:
Module:
M.Sc. Module Praktikum Maschinelles Lernen und Datenanalyse
The aim of this lab course is to practice the process of explorative data analysis and understand the main algorithms. The focus is on dimensionality reduction, clustering, classification and regression. For each assignment, a number of algorithms have to be implemented (in Matlab) and analyzed in experiments on real or synthetic data. Taking the Matlab course and the Machine Learning lecture is highly recommended but not a formal prerequisite.
The lab course consists of two parts: a lecture (Mondays at 10.15am), which is held only when a new assignment is handed out, and a consultation on Wednesdays (10.15am) in all following weeks. Please have a look at the calendar for the exact schedule.
Please register in the google group to receive announcements and ask questions.
More information can be found in the german Informationsblatt.
Schedule
See calendar
Material
Problem sheet #1 (Matlab), tests: U01_test_distmat.m,U01_test_mydet.m, PASS
Problem sheet #2 (unsupervised learning), Data: flatroll.mat, fishbowl_swissroll_correct.mat, U01_usps.mat. LLE slides. Tests: U02_tests.zip, PASS
Problem sheet #3 (Clustering, EM), English version, Data: U03_5gaussians.dat, U03_2gaussians.dat, PASS, Tests: U03_tests.zip
Problem sheet #4 (Classification: KRR, CV, ROC), English version, PASS, Tests: U04_test_CV_krr.m, Datasets
Literature
Lecture notes (as of April 2010)
Results
Matrikelnr. |
Sheet 1 |
Sheet 2 |
Sheet 3 |
Sheet 4 |
Sheet 5 |
305493 |
5 |
20 |
15 |
19 |
20 |
307336 |
5 |
20 |
18 |
18 |
20 |
306383 |
5 |
20 |
18 |
18 |
20 |
331086 |
5 |
22 |
20 |
18 |
20 |
310234 |
5 |
22 |
20 |
18 |
20 |
310260 |
5 |
17 |
19 |
20 |
15 |
311217 |
5 |
17 |
19 |
20 |
15 |
315728 |
5 |
18 |
20 |
20 |
20 |
314519 |
5 |
18 |
20 |
20 |
20 |
327898 |
5 |
20 |
20 |
15 |
18 |
329282 |
5 |
20 |
20 |
15 |
18 |
329499 |
5 |
20 |
20 |
20 |
20 |
329478 |
5 |
20 |
20 |
20 |
20 |
334450 |
5 |
21 |
21 |
15 |
20 |
335614 |
5 |
21 |
20 |
19 |
15 |
336016 |
5 |
21 |
20 |
19 |
15 |
Access to Matlab
The servers {bolero,pepino,fiesta}.cs.tu-berlin.de can be reached via ssh.