Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...
Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...
Abstract: Approximate nearest neighbor search (ANNS) is a key retrieval technique for vector database and many data center applications, such as person re-identification and recommendation systems. It ...
Abstract: Optimizing the K value in the K-Nearest Neighbor (KNN) algorithm is a critical step in enhancing model performance, particularly for tasks related to classification and prediction. The Elbow ...
Vicinity is a light-weight, low-dependency vector store. It provides a simple and intuitive interface for nearest neighbor search, with support for different backends and evaluation. There are many ...