Erinevus lehekülje "Machine learning ITI8565" redaktsioonide vahel

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[[Machine learning ITI8565]]
 
[[Machine learning ITI8565]]
  
Spring term 2022
+
Spring term 2025
  
 
ITI8565: Machine learning
 
ITI8565: Machine learning
  
Taught by: Sven Nõmm
+
Taught by: Prof. Sven Nõmm
 +
Teaching assistants Mr. Jaak Kapten and Mr. Mihhail Daniljuk
  
 
EAP: 6.0
 
EAP: 6.0
  
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Lectures on Tuesdays 12:15-13:45  U06a-209
The course will continue purely in online mode!!!
 
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Lectures on Tuesdays 13:45-15:15 Online only in MS Teams environment
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Practices on Thursdays 14:00-15:30 ICT-402
  
Practices on Thursdays 13:40-15:10 Online only in MS Teams environment
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Consultations is by appointment onlyPlease do not hesitate to ask for consultation!
 
 
Please use code HAL900  to join TalTech Moodle page of the course.
 
  
 +
Please refer to TalTech Moodle page of the course and MS Teams team of the course for up to date slides and files necessary for practice sessions. 
  
 
=Lectures =
 
=Lectures =
  
== Week 1  Introduction, Distance function ==
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This page will be populated during the term with lecture with the lecture slides.  
[[Media:Lecture_1_Intorduction_and_Distance_function_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 2  Cluster analysis I ==
 
[[Media:Lecture_02_Cluster_Analysis_1_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 3  Cluster analysis II (Probabilistic approach; Outlier and Anomaly Analysis) ==
 
[[Media:Lecture_03_1_Cluster_Analysis_2_Probabilistic_approachML_2022.pdf ‎|Slides]]
 
 
 
[[Media:Lecture_03_2_anomaly_and_otlier_analysis_ML2022.pdf ‎|Slides]]
 
 
 
== Week 4  Supervised learning I: Feature selection kNN and regression ==
 
[[Media:Lecture_04_Classification_1_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 5  Supervised learning II: Regression and decision trees ==
 
[[Media:Lecture_05_Supervised_Learning_2_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 6  Supervised learning III: Gradient descent ==
 
[[Media:Lecture_6_Gradient_descent_andmore_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 7  Supervised learning IV: Support Vector Machine ==
 
[[Media:Lecture_07_Support_Vector_Machines_Kernel_Trick_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 9  Supervised learning V: Model quality boosting ==
 
[[Media:Lecture_09_Model_Quality_Boosting_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 10  Supervised learning VI: Model quality boosting ==
 
[[Media:Markov model (1) (1).pdf ‎|Slides]]
 
 
 
== Week 11  Neural Networks I ==
 
[[Media: Lecture_11_Neural_Networks_ML_2022.pdf ‎|Slides]]
 
 
 
== Week 12  Neural Networks II ==
 
[[Media:Lecture_12_Neural_Networks_ML_2022.pdf ‎|Slides]]
 
  
== Week 13  Neural Networks III ==
 
[[Media:Lecture_13_Neural_Network_Intuition_ML_2022.pdf ‎|Slides]]
 
  
  

Viimane redaktsioon: 29. jaanuar 2025, kell 14:11

Machine learning ITI8565

Spring term 2025

ITI8565: Machine learning

Taught by: Prof. Sven Nõmm Teaching assistants Mr. Jaak Kapten and Mr. Mihhail Daniljuk

EAP: 6.0

Lectures on Tuesdays 12:15-13:45 U06a-209

Practices on Thursdays 14:00-15:30 ICT-402

Consultations is by appointment only! Please do not hesitate to ask for consultation!

Please refer to TalTech Moodle page of the course and MS Teams team of the course for up to date slides and files necessary for practice sessions.

Lectures

This page will be populated during the term with lecture with the lecture slides.


  • 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