Basics of Quantum Machine Learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10260385" target="_blank" >RIV/61989100:27740/25:10260385 - isvavai.cz</a>

Výsledek na webu

<a href="https://events.it4i.cz/event/354/" target="_blank" >https://events.it4i.cz/event/354/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Basics of Quantum Machine Learning

Popis výsledku v původním jazyce

This training course on the basics of Quantum Machine Learning (QML) explored the intersection of quantum computing and machine learning. It highlighted the advantages and potential applications of combining these two cutting-edge fields. The course built on foundational concepts of quantum computing and variational quantum algorithms, followed by an explanation of parameterised quantum circuits and their use in quantum classification and regression. It also examined quantum kernels in the support vector machine method and concluded with an introduction to quantum unsupervised machine learning. Each section included practical hands-on exercises to reinforce the discussed methods.

Název v anglickém jazyce

Basics of Quantum Machine Learning

Popis výsledku anglicky

This training course on the basics of Quantum Machine Learning (QML) explored the intersection of quantum computing and machine learning. It highlighted the advantages and potential applications of combining these two cutting-edge fields. The course built on foundational concepts of quantum computing and variational quantum algorithms, followed by an explanation of parameterised quantum circuits and their use in quantum classification and regression. It also examined quantum kernels in the support vector machine method and concluded with an introduction to quantum unsupervised machine learning. Each section included practical hands-on exercises to reinforce the discussed methods.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů