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Quantum Neural Networks (QNNs) with MATLAB

Discover how to implement quantum neural networks (QNNs) using MATLAB Support Package for Quantum Computing. This demonstration shows you how to train a hybrid quantum-classical neural network for a classification problem that is nonlinearly separable. Learn how to combine quantum computing and AI technologies within the MATLAB® ecosystem to tackle complex data problems efficiently.

Highlights:
- Understand the basics of QNNs and their applications.
- Learn how to set up and train a QNN using MATLAB.
- Explore the integration of quantum layers into classical neural networks.
- See how quantum computing can accelerate neural network training and performance.

Related Information:
- Quantum Computing with MATLAB: https://bit.ly/3zyLNEK
- Solve XOR Problem Using Quantum Neural Network: https://bit.ly/3CctFSC
- Deep Learning Onramp: https://bit.ly/3PKBVfh
- Introduction to Quantum Computing: https://bit.ly/3zyJ9ir
- List of Deep Learning Layers: https://bit.ly/4aaug47
- Define Custom Deep Learning Layer: https://bit.ly/4a5fP13
- Types of Quantum Gates: https://bit.ly/4h8BSpJ

Examples and How To:
- Quantum Monte Carlo Simulation: https://bit.ly/3zQhp9n
- Solve Max-Cut Problem Using QAOA: https://bit.ly/3DNU21W
- Ground-State Protein Folding Using Variational Quantum Eigensolver (VQE): https://bit.ly/3Whb92M

Chapters:
00:00 Introduction
00:28 Exploring the Example
01:08 Learn Neural Networks with MATLAB
01:28 Data and Task
01:56 How Quantum Computing Accelerates Neural Networks
03:46 How the Quantum Neural Network Works
08:47 Training and Testing Results
09:23 Summary
10:05 Call to Action

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