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About Intro To QMLand QNN
This document provides an introduction to quantum machine learning and quantum neural networks. It discusses how quantum machine learning aims to use quantum algorithms and properties like superposition and entanglement to solve machine learning problems that are intractable on classical computers. Specifically, it notes that many machine learning algorithms involve linear algebra operations that have exponentially faster quantum analogs. It then describes different types of quantum machine learning models, including deterministic and variational quantum neural networks. It discusses challenges like state preparation and input encoding to represent classical data on a quantum computer. Finally, it provides an overview of key concepts like model architecture, training methods, and unique challenges of quantum neural networks.
Detailed Information
| Author: | ['Seyyed Adnan Seyyedy'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 13 |
| Language: | English |
| Format: | |
| Price: | FREE |
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