Erinevus lehekülje "Machine learning ITI8565" redaktsioonide vahel
Mine navigeerimisribale
Mine otsikasti
| 54. rida: | 54. rida: | ||
[[Media: lecture_08_part_3_neural_networks_2_ML_2024.pdf |Slides part III]] | [[Media: lecture_08_part_3_neural_networks_2_ML_2024.pdf |Slides part III]] | ||
| − | == Week 10 | + | == Week 10 Sequential processes modelling: from Markov Models to LSTM == |
| − | |||
| − | == Week 12 Deep Learning I: | + | |
| − | + | == Week 12 Deep Learning I: Transformers== | |
| + | TBA | ||
== Week 13 Deep Learning II: Convolutional neural networks== | == Week 13 Deep Learning II: Convolutional neural networks== | ||
| − | |||
| − | == Week 14 Deep Learning | + | |
| − | + | == Week 14 Deep Learning III: Generative AI == | |
| + | |||
| + | |||
| + | == Week 15 Explainable AI== | ||
Redaktsioon: 25. märts 2024, kell 11:27
Spring term 2024
ITI8565: Machine learning
Taught by: Sven Nõmm
EAP: 6.0
Lectures on Tuesdays 12:00-17:00 ICT-A2
Practices on Thursdays 14:00-15:30 ICT-401
Consultations is by appointment only! Please do not hesitate to ask for consultation!
Some slides below are mostly from the year 2023. You are welcome to use this material as the reference but be aware that this year the course content will be revised and a few news topics will be added.
Lectures
Week 1 Introduction, Distance function
Week 2 Cluster analysis I
Week 3 Cluster analysis II (Probabilistic approach; Outlier and Anomaly Analysis)
Week 4 Supervised learning I: Classification
Week 5 Supervised learning II: Regression
Week 6 Supervised learning III: Gradient descent
Week 7 Supervised learning V: Model quality boosting
Week 8 Closed book test 1
Week 9 Neural Networks I
Slides part I Slides part II Slides part III
Week 10 Sequential processes modelling: from Markov Models to LSTM
Week 12 Deep Learning I: Transformers
TBA
Week 13 Deep Learning II: Convolutional neural networks
Week 14 Deep Learning III: Generative AI
Week 15 Explainable AI
- 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