I am totally new to artificial intelligence and neural networks and have a broad question that I hope is appropriate to ask here.
I am an ecologist working in animal movement and I want to use AI to apply to my field. This will be one of the few times this has been attempted so there is not much literature to help me here.
My dataset is binary. In short, I have the presence (1) and absence (0) of animal locations that are associated with a series of covariates (~20 environmental conditions such as temperature, etc.). I have ~1 million rows of data to train the model on with a ratio of 1:100 (presence:absence).
Once trained, I would like a model that can predict if an animal will be in a location (or give a probability) based on new covariates (environmental conditions).
Is this sort of thing possible using AI?
(If so, where should I be looking for resources? I write in R, should I learn Python?)