[ARCHIVED] A university quantum algorithms/computation course supplement based on Qiskit

Hands-On Graph Neural Networks Using Python, published by Packt

Code and Content for Manning Publication on Graph Neural Networks

The book A Methods Focused Guide to Quantum Error Correction and Fault-Tolerant Quantum Computation