Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)
Locality sensitive hashing (LSH) is a widely popular technique used in approximate nearest neighbor (ANN) search. The solution to efficient similarity search is a profitable one - it is at the core of several billion (and even trillion) dollar companies.

LSH consists of a variety of different methods. In this video, we'll be covering the traditional approach - which consists of multiple steps - shingling, MinHashing, and the final banded LSH function.

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00:00 Intro
01:21 Overview
05:58 Shingling
08:45 Vocab
09:27 One-hot Encoding
11:10 MinHash
15:51 Signature Info
18:08 LSH
22:20 Tuning LSH