Course detail
Machine Learning Fundamentals
FEKT-MPA-MLFAcad. year: 2021/2022
Quantum information is a basic entity in quantum information theory and can be manipulated using engineering techniques known as quantum information processing. As well as they can be processed by digital computers as classical information, transferred from place to place, manipulated and analyzed, similar concepts can be handled with quantum information. While the basic unit of classical information is a bit, in quantum information it is a qubit. Therefore, in computer exercises attention is paid to the processing of qubit.
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Course curriculum
2 - Basics of linear algebra for ML
3 - Support vectors, Support vector Machines
4 - Introduction to artificial neural networks, representation,
classification
5 - Neural network training (linear regression, Gradient method,
polynomial regression, ...)
6 - Convolutional neural networks
7 - Recursive neural networks
8 - Hyperparameter tuning, batch normalization and programming frameworks
9 - Learning without supervision
10 - Generative learning, autoencoders, GAN
11 - Machine learning on a large scale
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Classification of course in study plans
- Programme MPAJ-TEC Master's 1 year of study, summer semester, compulsory-optional