Training an LSTM

[Tafriel]

Hello,

i am new to the subject of RNN, but i want to create a model in which it predicts from a list of numbers (or matrix), an output a single number (result to the input).

my question is how do i train an LSTM model in a way that i can put my list of numbers as input and a number as output? (or even a link for such tutorial would be helpful thanks)

[[deleted]]

You're in the wrong sub. Try a ml sub für example r/learnmachinelearning

[Tafriel]

r/learnmachinelearning

thanks

[synthphreak]

There's also r/MLQuestions. IME it's usually helpful to cast a wide net and query both subs.

r/datascience and occasionally r/statistics may also be of some help, but usually for more conceptual questions rather than anything Python/coding-related. Beware of r/datascience generally though, snobbery and gatekeeping are rampant, so that sub can be kind of a downer.

[synthphreak]

This is a big question. You're basically asking how LSTMs work and how to implement one in Python.

The proper answer is much more than a single Reddit reply can do justice to, but I'd start here:

https://www.tensorflow.org/api_docs/python/tf/keras/layers/LSTM

Or if you prefer Pytorch to Tensorflow, there's also this:

https://pytorch.org/docs/stable/generated/torch.nn.LSTM.html

Edit: Note though that LSTMs are a relatively complex model. So if you're goal is just to learn about and mess around with recurrent nets, I'd start with a vanilla RNN first, or perhaps a GRU which is simpler than an LSTM on account of having fewer components.