Trainable, scalable quantum embedding kernels with variational parameters

Advanced Quantum Machine Learning project comparing Hybrid VQC and Quantum Kernel SVM for binary classification, featuring modular pipeline, PennyLane + PyTorch/Qiskit integration, and automatic artifact logging.

implement the quantum support vector machine for classification using pennylane framework

This project focuses on applying a Variational Quantum Circuit (VQC) for diabetes prediction using real-world medical data.

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.

Recurrent Neural Net built with PyTorch + trained on MNIST 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.