Erinevus lehekülje "Machine learning ITI8565" redaktsioonide vahel
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| 22. rida: | 22. rida: | ||
== Week 1 Introduction, Distance function == | == Week 1 Introduction, Distance function == | ||
[[Media:Lecture_1_Intorduction_and_Distance_function_ML_2022.pdf |Slides]] | [[Media:Lecture_1_Intorduction_and_Distance_function_ML_2022.pdf |Slides]] | ||
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| + | == Week 2 Cluster analysis I == | ||
| + | [[Media:Lecture_02_Cluster_Analysis_1_ML_2022.pdf |Slides]] | ||
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| + | == Week 2 Cluster analysis II (Probabilistic approach; Outlier and Anomaly Analysis) == | ||
| + | [[Media:Lecture_03_1_Cluster_Analysis_2_Probabilistic_approachML_2022.pdf |Slides]] | ||
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| + | [[Media:Lecture_03_2_anomaly_and_otlier_analysis_ML2022.pdf |Slides]] | ||
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Redaktsioon: 7. veebruar 2022, kell 15:41
Spring term 2022
ITI8565: Machine learning
Taught by: Sven Nõmm
EAP: 6.0
Lectures on Tuesdays 13:45-15:15 Online only in MS Teams environment
Practices on Thursdays 13:40-15:10 Online only in MS Teams environment
Please use code HAL900 to join TalTech Moodle page of the course.
More information will appear closer to the start of the spring term.
Lectures
Week 1 Introduction, Distance function
Week 2 Cluster analysis I
Week 2 Cluster analysis II (Probabilistic approach; Outlier and Anomaly Analysis)
- 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