Hey @psy!

How can I encode my data which is in the format of X … `X`

as a pandas data frame of shape [150,6]

If I’m interpreting your data’s dimensions properly, you have 150 samples of 6-dimensional data. So, you can definitely use something similar to the `interferometer`

function that is provided in the StrawberryFields QNN demo to encode a 6D feature, where each entry of the 6D vector are, say, angles of rotation. To get a simple example up and running, I recommend making a simpler function than `interferometer`

— just encode the data as angles of rotation.

and `y`

is a pandas series of length `150`

I’m not sure what the data you have represents, but you just need to make sure that your model’s output can be distilled down and compared to `y`

in some way that makes sense in the context of an objective function (what you’re trying to minimize).

How to train the CV Neural Network using my data?

It’s tough to give a great answer here because I’m not sure what your data represents. Having said that, whether it’s your data, our data, or someone else’ data, the same rules of training any quanutm neural network apply. If you’re still stuck, let me know

If the strawberry field is not working, can i just use pennylane inbuild CVNeuralNetwork class to do so ?

Are you referring to qml.CVNeuralNetLayers? If so, you can certainly use that as a template. Just please be aware that the PL-SF plugin is supported for versions <= v0.29 of PennyLane.

Lastly, please note that we are here to help you with your PennyLane and/or StrawberryFields code — give you ideas, inspiration, and pointers — but we can’t write the code for you. If you’re stuck on how to get started, we have a lot of great resources for that (see here for the SF tutorials: Tutorials — Strawberry Fields)

Hope this helps!