I have have a tabular data set that I am wanting to use for my features. It consists of numerical values and categorical variables that I have one hot encoded.
I want to but these features into a tensor but when i convert to a numpy array then try to place into a tensor it says an error due to the sparse vectors.
Is there another way to convert categorical variables instead of one hot encoding? I have seen people mention about nn.embeddings but not sure how that would work if my case if I am feeding in features with some numerical and some categorical
