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[[Machine learning ITI8565]]
 
[[Machine learning ITI8565]]
  
Spring term 2024
+
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
  
Lectures on Tuesdays 12:00-17:00 ICT-A2
+
Lectures on Tuesdays 12:15-13:45 U06a-209
  
Practices on Thursdays 14:00-15:30  ICT-401
+
Practices on Thursdays 14:00-15:30  ICT-402
  
 
Consultations is by appointment only!  Please do not hesitate to ask for consultation!  
 
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 =
 
=Lectures =
  
== Week 1  Introduction, Distance function ==
+
This page will be populated during the term with lecture with the lecture slides.  
[[Media:lecture_01_intorduction_and_distance_function_ml_2024_web_version.pdf ‎|Slides]]
 
 
 
== Week 2  Cluster analysis I ==
 
[[Media:lecture_02_cluster_analysis_1_ml_2024.pdf ‎|Slides]]
 
 
 
== Week 3  Cluster analysis II (Probabilistic approach; Outlier and Anomaly Analysis) ==
 
[[Media:lecture_03_1_cluster_analysis_2_probabilistic_approach_ml_2024.pdf ‎|Slides]]
 
 
 
[[Media:lecture_03_2_anomaly_and_otlier_analysis_ml_2024.pdf ‎|Slides]]
 
 
 
== Week 4  Supervised learning I: Classification ==
 
[[Media:lecture_04_classification_1_ml_2024.pdf ‎|Slides]]
 
 
 
== Week 5  Supervised learning II: Regression  ==
 
[[Media:lecture_05_supervised_learning_2_ml_2024.pdf ‎|Slides]]
 
 
 
== Week 6  Supervised learning III: Gradient descent ==
 
[[Media:lecture_06_Gradient_descent_andmore_ml_2024.pdf ‎|Slides]]
 
 
 
[[Media:lecture_06_Support_Vector_Machines_Kernel_Trick_ML_2024.pdf ‎|Slides]]
 
 
 
== Week 7  Supervised learning V: Model quality boosting ==
 
[[Media:lecture_07_Model_Quality_Boosting_ML_2024.pdf ‎|Slides]]
 
 
 
== Week 8  Closed book test 1 ==
 
 
 
== Week 9  Neural Networks I ==
 
[[Media: lecture_8_neural_networks_ML_2024.pdf ‎|Slides part I ]]
 
[[Media: Lecture_8_part_2_neural_networks_ML_2024.pdf ‎|Slides part II]]
 
[[Media: lecture_08_part_3_neural_networks_2_ML_2024.pdf ‎|Slides part III]]
 
 
 
== Week 10  Sequential processes modelling: from Markov Models to LSTM ==
 
 
 
 
 
== Week 11  Deep Learning I: Transformers==
 
TBA
 
 
 
== Week 12 Deep Learning II: Convolutional neural networks==
 
TBA
 
 
 
== Week 13 Deep Learning III: Generative AI ==
 
TBA
 
 
 
== Week 14 Explainable AI==
 
TBA
 
 
 
  
  

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