Hands-On Introduction to Quantum Machine Learning
This tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement). Building on that, foundational concepts of quantum machine learning (QML) are...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2024-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/135478 |
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| _version_ | 1849762720560185344 |
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| author | Muhammad Ismail Mohamed Shaban Samuel Yen-Chi Chen |
| author_facet | Muhammad Ismail Mohamed Shaban Samuel Yen-Chi Chen |
| author_sort | Muhammad Ismail |
| collection | DOAJ |
| description | This tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement). Building on that, foundational concepts of quantum machine learning (QML) are introduced (parametrized circuits, data encoding, and feature mapping). Then, QML models are discussed (quantum support vector machine, quantum feedforward neural network, and quantum convolutional neural network). All the aforementioned topics and concepts are examined using codes run on a quantum computer simulator. All the covered materials assume a novice audience interested in learning about QML. Further reading and software packages and frameworks are shared with the audience. |
| format | Article |
| id | doaj-art-c3068fbe1a37422abd70c00a9f9a5db8 |
| institution | DOAJ |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2024-05-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-c3068fbe1a37422abd70c00a9f9a5db82025-08-20T03:05:39ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622024-05-013710.32473/flairs.37.1.13547871851Hands-On Introduction to Quantum Machine LearningMuhammad Ismail0Mohamed Shaban1Samuel Yen-Chi Chen2Department of Computer Science, Tennessee Technological UniversityDepartment of Computer Science, Tennessee Technological UniversityWells FargoThis tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement). Building on that, foundational concepts of quantum machine learning (QML) are introduced (parametrized circuits, data encoding, and feature mapping). Then, QML models are discussed (quantum support vector machine, quantum feedforward neural network, and quantum convolutional neural network). All the aforementioned topics and concepts are examined using codes run on a quantum computer simulator. All the covered materials assume a novice audience interested in learning about QML. Further reading and software packages and frameworks are shared with the audience.https://journals.flvc.org/FLAIRS/article/view/135478 |
| spellingShingle | Muhammad Ismail Mohamed Shaban Samuel Yen-Chi Chen Hands-On Introduction to Quantum Machine Learning Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| title | Hands-On Introduction to Quantum Machine Learning |
| title_full | Hands-On Introduction to Quantum Machine Learning |
| title_fullStr | Hands-On Introduction to Quantum Machine Learning |
| title_full_unstemmed | Hands-On Introduction to Quantum Machine Learning |
| title_short | Hands-On Introduction to Quantum Machine Learning |
| title_sort | hands on introduction to quantum machine learning |
| url | https://journals.flvc.org/FLAIRS/article/view/135478 |
| work_keys_str_mv | AT muhammadismail handsonintroductiontoquantummachinelearning AT mohamedshaban handsonintroductiontoquantummachinelearning AT samuelyenchichen handsonintroductiontoquantummachinelearning |