Reproducible QML benchmark: VQC vs QSVM on binary tasks. Modular, cross-platform pipeline w/ artifact logging.
Trainable, scalable quantum embedding kernels with variational parameters
implement the quantum support vector machine for classification using pennylane framework
This repository tackles the Banknote Authentication binary classification problem using both classical and quantum machine learning. Classical models (MLP) are implemented with scikit-learn and Keras, while a single-qubit variational circuit is built with Qiskit to compare performance.
This project focuses on applying a Variational Quantum Circuit (VQC) for diabetes prediction using real-world medical data.
An amygdala hijack is a sudden, intense, and disproportionate emotional response to a situation that triggers the fight-or-flight response. It happens when the amygdala, a part of the brain that controls emotions and memories, takes over and disables the frontal lobes, which regulate rational thought,This project aims to give solutions related to.
Recurrent Neural Net built with PyTorch + trained on MNIST data
Add a description, image, and links to the quantummachinelearning topic page so that developers can more easily learn about it.
To associate your repository with the quantummachinelearning topic, visit your repo's landing page and select "manage topics."