I would like to build a model that can classify a "sample" of data which is a time series dataset. Basically it's a sequence of data from T1 -> Tn. I have a lot of separate samples that look like T1 -> Tn. Say they came from an IOT device that tracked tire pressure or something. Each sample would have a different number of data points. So sample 1 could have 500, and sample 2 could have 2000. I've done some research on here on similar problems but have not seen any answers. Namely, I've read these posts that have no answers post1 and post2. This post seems similar to what I'm trying to do but I'm not even sure how to achieve it. Is there a way someone can describe how to do this? Or can someone point me in the direction of some article/book that will have a description of how to do this?