Labs

Datum	Č.T.	S/L	Náplň	Učitel	Materiály
19-21.09.2022	1	S	Intro: Python, Numpy, Pytorch intro - Home exercise!	SP + PS	NumPy & PyTorch tutorial
26-28.09.2022	2	L	Regression: Backpropagation in computational graphs	KZ	labs_02_regression.pdf template_for_students.zip HW1 - UPLOAD THE FULL ZIP TO BRUTE! (7b) lab2_recording
03-05.10.2022	3	S	Classification: 1D/2D, 0/1 MNIST classifier, derive logistic loss	PV	class1.tar
10-12.10.2022	4	L	Convolution: 1D/2D convolution, blurring filter, edge detection, ReLu, computational graphs	PV	HW2 (13b) 1D Conv video
17-19.10.2022	5	S	Optimizers: convergence rate, oscillations, diminishing gradients,	KZ	optimizers_student_template.py.zip
24-26.10.2022	6	L	Deep ConvNet I: typical structure, ImageNet classifier, using GPU	SP + PS	HW3: Image classification (13b) lab6.zip lab6_ref.zip
31-02.11.2022	7	S	Deep ConvNet II: Receptive fields, BatchNorm, Skip connections	JC	batch norm Araujo et al.
07-09.11.2022	8	L	Segmentation: Net surgery - exploit previously trained classifier.	SP + PS	HW4: Image segmentation (17b) lab8.zip
14-16.11.2022	9	S	Work on Homeworks (optional consultations upon an email request)	SP + PS
21-23.11.2022	10	L	Work on Homeworks (optional consultations upon an email request)	SP + PS
28-30.11.2022	11	S	GAN I: DCGAN for CelebA dataset	DC	lab_assignment HW5 (10b)
05-07.12.2022	12	L	GAN II: ???	DC
12-14.12.2022	13	S	Advanced backpropagation methods: Backprop through optimization layer and/or RL	KZ
09-11.01.2023	15	S	Presentation of semestral works and feedback	KZ