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.
Requirements
A little background in either variational quantum algorithms or classical machine learning is useful but optional.
While a basic knowledge of quantum computing (gates, circuits, measurements) is expected, a crash course can be included to the programme, or given as a separate lecture prior to the event.
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.