Open hertschuh opened 1 month ago
We have used TensorFlow Recommenders (TFRS) to generate sets of recommended content for users. We are mostly optimizing for user clicks, so the problem is binary classification. (We want to present content to users that they will click.) Here are some capabilities that are important to us:
The primary challenge we have faced with TFRS is that the deployed models do not scale well; We have a custom multi-model endpoint that first invokes the retrieval model, then cross joins the retrieved items with the users, then invokes the ranking model. The endpoint times out or runs out of memory when we invoke it with millions of queries.
Keras Recommenders (Keras-RS)
We are considering building Keras Recommenders, a multi-backend (TensorFlow, JAX, PyTorch) Keras 3 based library to ease the development of recommender models.
We want your feedback on features you think would be useful to have.
Please comment below.