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b251
courses
becm33dpl
tutorials
Labs
The labs have the same structure as
B3B33UROB
course
UROB Course github
UROB Course pages
Lab schedule
Date
Week
Topic
Resources
Homework assignment
24.9.2025
1
Intro:
Introduction to the course and machine learning.
Classification
1.10.2025
2
1D regression and 2D classification:
Revision of the regression and classification theory, analytic gradient computation, gradient in computational graph and loss minimization.
template_for_students.zip
labs_02_regression.pdf
8.10.2025
3
Loss, MLP
HW01 - MLP
15.10.2025
4
Autograd:
Computational graphs, backpropagation and the automatic gradient computation.
lab04.zip
lab04.pdf
lab04_ref.zip
22.10.2025
5
Labs cancelled (ICCV 2025)
HW01 deadline
29.10.2025
6
CNN:
Introduction to convolution and convolution neural networks
lab05.zip
lab05_ref.zip
HW02 - Autograd
5.11.2025
7
Training of neural networks
lab06.zip
lab06_solved.zip
12.11.2025
8
Layers of Neural Networks
lab7.zip
HW02 deadline
HW03 - segmentation
19.11.2025
9
Optimization:
Convergence rate, oscillations, diminishing gradients.
lab8.zip
26.11.2025
10
Transformers I:
Introduction to the transformer architecture, GPT2
lab10.zip
3.12.2025
11
Transformers II:
Intro into ViTs
HW03 deadline
HW04 - Transformers
10.12.2025
12
RL I Intro:
Introduction to the reinforcement learning. Policy gradient.
rl_lab_1.pdf
17.12.2025
13
RL II - Deep learning:
Deep reinforcement learning.
HW04 deadline
HW05 - RL
7.1.2026
14
HW05 deadline
courses/becm33dpl/tutorials/start.txt
· Last modified: 2025/11/26 12:14 by
skvrnjan