AWS Quantum Technologies Blog
Author: Riccardo Nembrini
Riccardo Nembrini is a PhD Student in Information Technology at Politecnico di Milano, with a scholarship sponsored by ContentWise. His research focuses on current Quantum Computing technologies and their application to Optimization and Machine Learning problems. In particular, he mainly works with Quantum Annealing and recently applied this technology on a Feature Engineering problem in Recommender Systems.
Implementing a Recommendation Engine with Amazon Braket
In this blog post, we detail an approach to solving a feature selection problem that implements a recommendation engine using Amazon Braket – the quantum computing service by Amazon Web Services. Our approach tackles the “cold-start” problem that recommendation systems face, produces a solution comparable with traditional approaches, and reaches the required levels of accuracy […]