Maciej Kula - Speeding up search with locality sensitive hashing

Maciej Kula - Speeding up search with locality sensitive hashing
[EuroPython 2015]
[24 July 2015]
[Bilbao, Euskadi, Spain]

Locality sensitive hashing (LSH) is a technique for reducing complex
data down to a simple hash code. If two hash codes are similar than
the original data is similar. Typically, they are used for speeding up
search and other similarity comparisons.

In this presentation I will discuss two ways of implementing LSH in
python; the first method is completely stateless but only works on
certain forms of data; the second is stateful but does not make any
assumptions about the distribution of the underlying data. I will
conclude the presentation by describing how we apply LSH to search at
Lyst.

Видео Maciej Kula - Speeding up search with locality sensitive hashing канала EuroPython Conference