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[[Machine learning ITI8565]]
 
[[Machine learning ITI8565]]
  
Spring term 2021
+
Spring term 2022
  
 
ITI8565: Machine learning
 
ITI8565: Machine learning
9. rida: 9. rida:
 
EAP: 6.0
 
EAP: 6.0
  
NB! At least in the beginning of the spring term all teaching will be conducted online.
 
Please joint MS Teams! Team name Machine learning ITI8565; Spring term 2021  The code to join the team is '''gkq6q3q'''
 
It is recommended to download and install MS Teams as standalone application and login there with TalTech UniID account. 
 
  
 +
Lectures on Tuesdays 13:45-15:15  ICT-315
  
Lectures on Tuesdays 14:00 - 15:30 Online in MS Teams
+
Practices on Thursdays 13:40-15:10 ICT-401
 
 
Practices on Thursdays 17:45 - 19:15  Online in MS Teams
 
  
  
22. rida: 18. rida:
  
 
== Week 1  Distance function ==
 
== Week 1  Distance function ==
[[Media:Lecture_1_Intorduction_and_DistanceFunction_ML_2021.pdf ‎|Slides]]
 
 
== Week 2  Cluster analysis I ==
 
[[Media:Lecture_02_Cluster_Analysis_1_ML_2021.pdf ‎|Slides]]
 
 
== Week 3  Cluster analysis II ==
 
[[Media:Lecture_03_Cluster_Analysis_2_Probabilistic_approachML_2021.pdf ‎|Slides]]
 
 
== Week 3  Anomaly and outlier analysis ==
 
[[Media:Lecture_04_anomaly_and_otlier_analysis_ML2021.pdf ‎|Slides]]
 
 
== Week 4  Supervised Learning I ==
 
[[Media:Lecture_05_Classification_1_ML_2021.pdf ‎|Slides]]
 
 
== Week 5  Supervised Learning II ==
 
[[Media:Lecture_06_Classification_2_ML_2021.pdf ‎|Slides]]
 
 
NB! Home assignment 1 will be distributed during the practice on 25.02.2021
 
 
== Week 6  Supervised Learning III ==
 
[[Media:Lecture_7_Gradient_descent_andmore_ML_2021.pdf ‎|Slides]]
 
 
== Week 7  ==
 
 
Closed book test on 16.03.2021
 
 
Defense of Home assignment I on 18.03.2021
 
 
== Week 8  Supervised Learning IV ==
 
[[Media:Lecture_8_Supervised_learning_IV_NaiveBayes_ML_2021.pdf ‎|Slides]]
 
 
 
== Week 9  Supervised Learning IV ==
 
[[Media:Lecture_9_Support_Vector_Machines_Kernel_Trick_ML_2021.pdf ‎|Slides]]
 
 
== Week 10  Supervised Learning V; Neural Networks ==
 
[[Media:Lecture_10_Neural_Networks_ML_2021.pdf ‎|Slides]]
 
 
[[Media:Lecture_10_part2_Neural_Networks_ML_2021.pdf ‎|Slides]]
 
 
== Week 11  Competitive learning ==
 
[[Media:Lecture_11_Neural_Networks_ML_2021.pdf ‎|Slides]]
 
 
== Week 12  XOR Neural networks ==
 
[[Media:Lecture_12_Neural_Networks_ML_2021.pdf ‎|Slides]]
 
 
== Week 13  Boosting the model quality ==
 
[[Media:Lecture_13_Model_Quality_Boosting_ML_2021.pdf ‎|Slides]]
 
 
== Week 14  Hidden Markov Models ==
 
[[Media:Lecture_14_Hidden_Markov_Models_ML2021.pdf ‎|Slides]]
 
  
== Week 15  Introduction to Deep learning ==
 
[[Media:Lecture_15_Deep_Learning_ML_2021.pdf ‎|Slides]]
 
  
 
*91 < score      -- grade 5 (excellent)
 
*91 < score      -- grade 5 (excellent)

Redaktsioon: 8. jaanuar 2022, kell 19:35

Machine learning ITI8565

Spring term 2022

ITI8565: Machine learning

Taught by: Sven Nõmm

EAP: 6.0


Lectures on Tuesdays 13:45-15:15 ICT-315

Practices on Thursdays 13:40-15:10 ICT-401


Lectures

Week 1 Distance function

  • 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