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How to approach a neural-net based recommendation system problem in RapidMiner?
Newbie
Hi,
I was trying out new things, but I was stuck at this problem. I want to build a product recommendation system on rapidminer based on user and product ids, using a neural net based approach to first project. them into a latent space using autoencoder. I saw the k-nn algorithm tutorial but I need to used embedding layer for my use. I tried but from my understanding I can only import the embedding layer right? The one in the deep learning extension? Or am I missing something?
I would really appreciate your help. Any basic process to get me started.
Thank you.
I was trying out new things, but I was stuck at this problem. I want to build a product recommendation system on rapidminer based on user and product ids, using a neural net based approach to first project. them into a latent space using autoencoder. I saw the k-nn algorithm tutorial but I need to used embedding layer for my use. I tried but from my understanding I can only import the embedding layer right? The one in the deep learning extension? Or am I missing something?
I would really appreciate your help. Any basic process to get me started.
Thank you.
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