Information regarding course evaluation


  • It is not necessary for you to have participated at the Neural Network optional class from the 3rd year.

  • In order to pass the laboratory you need at least 35 points from 100

  • In order to pass the course you need at least 35 points from 100

  • The final grade is computed according the following formula: 0.6*(Laboratory Grade) + 0.4 *(Exam Grade)

  • Points for the laboratory part are obtained by presenting homework during the laboratory classes

  • Points for the course part are obtained at the end of the semester by passing the exam.

curs1 master 2021

Course 1

Machine Learning Concepts. Types of neurons

video link: https://youtu.be/xVzJKtzeons

curs2 2021

Course 2

The perceptron algorithm

video link:
https://youtu.be/4LHaieIiSWY

curs3 2021

Course 3

The backpropagation algorithm

video link:
https://youtu.be/VtxGi7u41kY

curs4 2021

Course 4

Cross Entropy, Softmax, Weight Initialization

video link:
https://youtu.be/ID4kgYijub8

Curs5 2021

Course 5

Solutions to overfitting

video link:
https://youtu.be/3EOcHuerjJA

Curs6 2021

Course 6

Optimisers

video link:
https://youtu.be/EyRUyXufKxg

CARN - curs7 2021

Course 7

Other activation functions

video link:
https://youtu.be/cen8EwArj20

curs8 2021

Course 8

Convolutional Neural Networks

video link:
https://youtu.be/UUzCvJ5COK4

curs9 2021

Course 9

Recurrent Neural Networks. LSTM

video link:
https://youtu.be/gtPk6vhD1EE

Curs10 2021

Course 10

Residual Neural Networs; Inception

video link:
https://youtu.be/X4R3Zua8R78

Curs11 2021

Course 11

Generative Adversorial Networks

video link:
https://youtu.be/LiIvzMDaTQQ