Is it possible to train numeric data using transfer learning?

I did research on learning large amounts of numeric data with RNN (LSTM).

The results were pretty accurate.

However, recently, I would like to compare result CNN and transfer learning.

I have studied many matlab examples documents and search on google.

However, I couldn't find an example of learning 'double(numeric)' data. Everything is for images.

So my question is, is it possible learn double data using transfer learning? If so, can you give me an example or material I can refer to?

I really sorry for the worst English skills.

Thank you.

Answer 1

[Walter Roberson]

Yes, it is possible to use transfer learning for non-image data.

For example https://becominghuman.ai/unsupervised-pre-training-for-speech-recognition-wav2vec-aba643824324?gi=f24550e74b12 specifically says that it can be done, and has a link to python code for the purpose.

The concepts are the same as for image recognition; the problem is finding a pre-trained network that can be usefully adapted for your purposes.

[Byung - Gi Jeon]

Thank you Roberson. I was a great help.

I`m weak at python so I wanted to implement it in matlab. But I`ll try.

Thank you so much for finding good doc. once again.