An Introduction to Quantum Machine Learning for Engineers
Overview & Synopsis
This monograph provides a self-contained introduction to Quantum Machine Learning for an audience of engineers with a background in probability and linear algebra. It first describes the necessary background, concepts, and tools necessary to describe quantum operations and measurements. Then, it covers parametrized quantum circuits, the variational quantum eigensolver, as well as unsupervised and supervised quantum machine learning formulations.
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Document Information
| Document Title | An Introduction to Quantum Machine Learning for Engineers |
|---|---|
| Author / Organization | Osvaldo Simeone |
| Subject & Discipline | Machine Learning, Quantum Computing, Neural Networks and Deep Learning, Artificial Intelligence, Data Analysis and Data Mining |
| Categories | Machine Learning |
| Publication Year | 2022 |
| ISBN | 1638280584 |
| License / Rights | Creative Commons License (CC) |
| Resource Verification | Access Restricted / Protected Host |
| Alternative Mirrors & Links | |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Language | ENGLISH |
| Catalog ID | DOC-10560 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |
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