Feature request: Creating an Quantum Circuit Probability Predictor using concepts of advanced Machine Learning

[Panchadip-128]

Is your feature request related to a problem? Please describe.
The Quantum Circuit Probability Predictor is a machine learning-based application designed to predict the probability of measuring a specific quantum state after applying a series of quantum gates to a qubit. Leveraging the principles of quantum mechanics and classical machine learning, this project aims to create a robust model that accurately estimates the probabilities associated with different quantum states resulting from varied input parameters.

Describe the solution you'd like
A machine learning model is trained on the computed probabilities to predict outcomes for angles not seen during training, enabling the model to generalize well to new inputs.

Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.

Approach to be followed (optional)
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Additional context
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[github-actions]

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[github-actions]

This issue has been automatically closed because it has been inactive for more than 30 days. If you believe this is still relevant, feel free to reopen it or create a new one. Thank you!