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

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