Approximate Nearest Neighbours in FAISS: Cell Probe 101
In this video, we will learn about the capabilities of Facebook's FAISS library in the context of vector search. We will discuss the technical framework of Approximate Nearest Neighbours and its implementation using Cell Probe methods. We will illustrate this with a visualization of 10,000 2D arrays and detail how the vector space is partitioned.
Additionally, we'll explain the role of the K-means algorithm in FAISS's partitioning process, the steps to train your index, and methods to identify centroids that denote the cells.
#FAISS #VectorSearch #NearestNeighbours #CellProbeMethods #DataVisualization #MachineLearning #FacebookAI #KmeansAlgorithm #BruteForceSearch #AIExplained
Blog: https://www.markhneedham.com/blog/202...
Notebook: https://github.com/mneedham/LearnData...