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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

Artificial Intelligence

The course is not on the list Without time-table
Code Completion Credits Range Language
2312014 KZ 2 2+0 Czech
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Department of Mechanics, Biomechanics and Mechatronics
Synopsis:

Tasks and challenges of Artificial Intelligence (AI), history of AI, Turing?s, Minsk?s and Kotek?s definitions of AI, approaches of mathematical logic. SW and HW tools for rapid prototyping and implementation of AI, commercial vs. open-source tools, modern AI trends (CUDA, neuromorphic HW, cloud technologies). Production systems, knowledge representation and expert systems, recommender systems. AI based on machine learning and data processing, an overview of computational intelligence tools for AI. Classification, decision trees, tree algorithms, gradient boosting. Neural Networks (NS), division, basic concepts and principles, shallow vs. deep NS (Deep Learning). Incremental and batch supervised machine learning algorithms, (Levenberg-Marquardt, Conjugate Gradients, Entropy Criterion Functions). Linear and Polynomial Neural Architectures, MLP, Extreme Machine Learning, Echo State NS. Data clustering, self-organizing maps (SOM). Dimensionality Reduction, PCA, Auto Encoder, Convolution Network, Deep Learning, Deep Neural Networks. Indefinite information and uncertainties in data. Fuzzy logic and fuzzy sets, fuzzy rule systems, neuro-fuzzy systems. Type-2 fuzzy sets, Type-2 uncertainty in relation to the data measurement.

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Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2019-09-16
For updated information see http://bilakniha.cvut.cz/en/predmet5465206.html