Locality Sensitive Hashing for Search with Shingling + MinHashing - Python

Explore the fundamentals of Locality Sensitive Hashing (LSH) for efficient similarity search in this 27-minute video tutorial. Dive into the traditional LSH approach, covering essential steps such as shingling, MinHashing, and the final banded LSH function. Learn how these techniques are utilized by major tech companies for approximate nearest neighbor (ANN) search. Follow along as the instructor breaks down complex concepts, including one-hot encoding, vocabulary creation, and signature information. Gain insights into tuning LSH for optimal performance and understand its applications in various industries. Enhance your knowledge of this powerful technique that forms the core of several successful businesses in the tech world.

Intro
Overview
Shingling
Vocab
One-hot Encoding
MinHash
Signature Info
LSH
Tuning LSH