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[[Machine learning ITI8565]] | [[Machine learning ITI8565]] | ||
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| + | Previous years: [https://courses.cs.ttu.ee/pages/Machine_learning (2017)] | ||
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| + | Spring 2016/2017 | ||
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| + | ITI8565: Machine learning | ||
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| + | Taught by: Sven Nõmm | ||
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| + | EAP: 6.0 | ||
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| + | Time and place: | ||
| + | Lectures: Tuesdays 16:00-17:30 ICT-A1 | ||
| + | Labs: Thursdays 16:00-17:30 ICT-402 | ||
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| + | Consultation: There is no scheduled time for consultation this semester. If you need consultation just drom me an e-mail and I will find time to answer your questions! | ||
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| + | Additional information: sven.nomm@ttu.ee | ||
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| + | ==Evaluation== | ||
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| + | *91 < score -- grade 5 (excellent) | ||
| + | *81 < score < 90 -- grade 4 (very good) | ||
| + | *71 < score < 80 -- grade 3 (good) | ||
| + | *61 < score < 70 -- grade 2 (satisfactory) | ||
| + | *51 < score < 60 -- grade 1 (acceptable) | ||
| + | score ≤ 50 -- a student has failed the course | ||
| + | |||
| + | =Lectures = | ||
| + | Lecture slides, necessary files, links and other necessary information would be provided by means of Moodle (To be set up by 10.02.2017) | ||
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| + | == Lecture 1: Intro == | ||
| + | [[Media:Intro_and_DTrees_ML2017_1.pdf |Slides]] | ||
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| + | == Lecture 2: Distance and classification == | ||
| + | [[Media:Lecture2_ML2017_kNN.pdf |Slides]] | ||
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| + | == Lecture 3: Clustering I == | ||
| + | [[Media:Lecture3_ML2017_Clustering.pdf |Slides]] | ||
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| + | == Lecture 4: Clustering II == | ||
| + | [[Media:Lecture4_ML2017_Clustering2.pdf |Slides]] | ||
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| + | Moodle environment at ained.ttu.ee has been updated. | ||
Redaktsioon: 29. jaanuar 2018, kell 13:51
Previous years: (2017)
Spring 2016/2017
ITI8565: Machine learning
Taught by: Sven Nõmm
EAP: 6.0
Time and place:
Lectures: Tuesdays 16:00-17:30 ICT-A1 Labs: Thursdays 16:00-17:30 ICT-402
Consultation: There is no scheduled time for consultation this semester. If you need consultation just drom me an e-mail and I will find time to answer your questions!
Additional information: sven.nomm@ttu.ee
Evaluation
- 91 < score -- grade 5 (excellent)
- 81 < score < 90 -- grade 4 (very good)
- 71 < score < 80 -- grade 3 (good)
- 61 < score < 70 -- grade 2 (satisfactory)
- 51 < score < 60 -- grade 1 (acceptable)
score ≤ 50 -- a student has failed the course
Lectures
Lecture slides, necessary files, links and other necessary information would be provided by means of Moodle (To be set up by 10.02.2017)
Lecture 1: Intro
Lecture 2: Distance and classification
Lecture 3: Clustering I
Lecture 4: Clustering II
Moodle environment at ained.ttu.ee has been updated.