I’ve been reading about TensorFlow for a few days now but it’s pretty overwhelming and I’m at that stage where everything I read makes me more confused and I need to get my foot in the door. I’m trying to use AI as part of a project I’m working on and maybe use it for other things in the future.
So what I’m working on needs to perform classification on time series. Most time series stuff is about forecasting, and what little I’ve found on time series classification only seems to have one attribute. I have multiple time series which have about 45 columns and about 250 rows and I’m reading them in from an SQL database and I will put them into NumPy for TF to use. I also have a few other little bits of data which may help with the prediction but aren’t really part of the time series. So each example will consist of a 45×250 array and a 3×1 array. How do I start with this?
I understand Flatten will turn the big array into a 11250×1 array, then I could (somehow) join it with the 3×1 array. Will this mess anything up? Does TensorFlow need to understand that these are values that are changing over time or does it not care?
I also have a column which has the day of the week in text, do I need to do something with this so that TF understands it? I figure I need to turn it into an integer but then TF needs to understand that it only goes from 1 – 7 and that after 7 it loops back to 1, rather than 8.
Last of all I need to understand how to build my neural network but don’t really have a clue how to do this. are there any recommended guides out there for someone who’s coming from a Python programming background rather than a statistical analysis background?
Sorry for the stupid questions, I appreciate any help I can get.