With recent success of artificial neural networks and emergence of Near
Intermediate Scale Quantum computers a new field of quantum machine
learning was established. There is hope that quantum computers will be
able to build better and faster machine learning models. One of the
quantum machine learning approaches is to embed quantum computers into
neural network processing graphs. During the talk I will present the
basic concepts of quantum neural networks, their training and
application in multi-class supervised classification setting. I will
show how to use two python libraries, namely: scikit-learn and pennylane
to perform training and inference using a particular type of a quantum
neural network.
[https://pgawron.github.io/](Homepage)
[https://astrocent.camk.edu.pl/contact/professor-piotr-gawron/](AstroCeNT)
Video Recording of the talk:
https://durham.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?tid=16296b66-11aa-47d5-a9c5-ac0800eb1028