Scalable Quantum Neural Network builds and trains a large-scale QNN in a modular fashion. SQNN is evaluated with a binary classification task on the MNIST dataset.

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.

This repository combines all the codes to produce the plots and results from the following article: arXiv:2404.16541

A predictive algorithm to forecast the weather, chances of rain in particular, using a quantum approach.

Qiskit Fall Fest Kolkata Chapter Hackathon 2022 Project on QML

Implementation of a Variational Quantum Classifier (VQC) to predict heart disease, created as the capstone project for the IBM and Freeya Mind Campus’ Road to Practitioner program.

Quantum Machine Learning (QML) project that predicts suitable crops based on soil and environmental parameters using quantum-enhanced models. Built as a hybrid application combining classical preprocessing with quantum circuits (via Qiskit/PennyLane), this app demonstrates how quantum computing can be applied to real-world agricultural challenges.

A modular quantum computing library in Python featuring QAOA, Grover, HHL, and VQC — built on Qiskit, with future plans to become a QPU-agnostic, from-scratch quantum SDK.