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.
Course 1
Machine Learning Concepts. Types of neurons
video link: https://youtu.be/xVzJKtzeons
Course 3
The backpropagation algorithm
video link: https://youtu.be/VtxGi7u41kY
Course 4
Cross Entropy, Softmax, Weight Initialization
video link:https://youtu.be/ID4kgYijub8
Course 5
Solutions to overfitting
video link:https://youtu.be/3EOcHuerjJA
Course 6
Optimisers
video link:https://youtu.be/EyRUyXufKxg
Course 8
Convolutional Neural Networks
video link: https://youtu.be/UUzCvJ5COK4
Course 10
Residual Neural Networs; Inception
video link: https://youtu.be/X4R3Zua8R78
Course 11
Generative Adversorial Networks
video link: https://youtu.be/LiIvzMDaTQQ