A guided hike into quantum machine learning
Salle de formation
Maison de la Simulation
Description
An introduction to quantum machine learning.
With cool pictures!
With memes!
With food!
The lecture will cover a basic introduction to quantum neural networks, quantum kernels, and data encoding techniques, with hands-on sessions for each. More advanced topics such as barren plateaus, expressivity, and "application <-> hardware" pipelines will be brushed over but not covered in detail.
Attendance
In-person: The training will be held at Maison de la Simulation, CEA Saclay, building 565 PC 190 – Digiteo, 91191 Gif-sur-Yvette, France.
Remote: A video broadcast will be set up. The link will be posted here a few days before the event.
Requirements
A little background in either variational quantum algorithms or classical machine learning is useful but optional.
A basic knowledge of quantum computing (gates, circuits, measurements) is expected.
Software tools
We will use Python during the hands-on sessions. You are free to use the quantum SDK of your choice. Nonetheless, it is strongly recommended that you install Xanadau's PennyLane; Qiskit is also supported. Please make sure that you can run this example code, or reproduce it using the SDK of your choice.
Acknowledgements
This event is supported by the QEC4QEA project and the European Union.
