So, im working on a project where i am leveraging ai to get accurate price predictions in terms of houses and real estate properties. I would like to use an artificial neural network so now i have to figure out where to start and how to figure out how many layers i should use, as well as the number of nodes in each layers.

I have a dataset of approx 15k rows as well as 153 features and then the label which is the price (what i want to predict). Im thinking of building a small scale model, training it on 3000 rows (this includes, train, cross validation and testing). Later on i will scale it depending on how the small model performs.

Do you guys have any suggestions or advice on how to go about this? Thank you guys



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