Hi Josep!



 titoniubo:

So far I try (note I have 10 variables and 3 outputs):
X_train = np.array(X_train, dtype=np.float32)
X_train.shape
...

I’d appreciate if you could let me know if my reasoning is correct.


I’m not sure what you are trying to do here.
First, you need to package your input data as a pytorch tensor.
(That’s what pytorch works with.)
You need a batch size.  It can be 1, if you want to work with a single
sample, but let’s say you use a batch size of 7.  Then a single batch
of your input data should be a pytorch tensor of shape (7, 10).  The
first row of this tensor will be one sample consisting of the values of
your 10 variables.
For regression (in contrast to a more full-featured neural network)
you would train the weights of s single Linear layer so that its
outputs best match your target value.
So you should instantiate nn.Linear (10, 3) as your “model”.
See if you can write a simple script that packs some data into a
tensor of the appropriate shape and successfully passes it through
a single Linear.
If you have issues, feel free to post the complete script, together
with any error messages or incorrect / unexpected output, and
forum participants will likely be able to help you further.
Good luck.
K. Frank