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by Meta · 0 reviews

An open-source deep learning architecture for recommendation systems that combines dense and sparse features through embedding tables, interaction layers, and MLP components, used for CTR prediction and personalization.

by scikit-learn · 0 reviews

An efficient unsupervised anomaly detection algorithm that isolates anomalies through random partitioning, robust to high-dimensional data.

by Steffen Rendle · 0 reviews

A supervised learning implementation of factorization machines for classification, regression, and ranking that captures feature interactions, widely used in recommendation systems.

by scikit-learn · 0 reviews

An unsupervised anomaly detection method that computes local density deviations to detect anomalies relative to neighboring points.

by Huawei Noah's Ark Lab · 0 reviews

An end-to-end wide-and-deep learning framework combining factorization machines and neural networks for click-through-rate prediction.