Welcome to the forum @ilkayn!

Great demo suggestions @sophchoe and @NikSchet! Just to complement, I add a few thoughts here.

If you only know the basics of quantum computing I would suggest the following guidelines:

- Your quantum version of this model will probably be a quantum-classical hybrid in fact.
- The quantum part will be contained into what we call a
**qnode** in PennyLane.
- Your qnode will receive some fixed inputs and some variable parameters. The inputs will have to be encoded in your circuit and the parameters will go into gates in your circuit. Part of the question is to choose how you will encode the data and how you will decide which gates to use in your circuit.
- You can interface classical layers in Keras or Torch with quantum layers using PennyLane.

I encourage you to check out this blog on how to start learning quantum machine learning, and if you want to do a deeper dive into quantum computing the Xanadu Quantum Codebook is a great resource.

You can also find a lot of additional tutorials on the PennyLane website in the **QML** section, and some PennyLane tutorial videos in the Xanadu YouTube.

I hope this helps and please post any follow-up questions you get!