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.

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