There are 2 repositories under count-min-sketch topic.
Probabilistic data structures for processing continuous, unbounded streams.
JS implementation of probabilistic data structures: Bloom Filter (and its derived), HyperLogLog, Count-Min Sketch, Top-K and MinHash
C++ Implementations of sketch data structures with SIMD Parallelism, including Python bindings
Sketching Algorithms for Clojure (bloom filter, min-hash, hyper-loglog, count-min sketch)
Probabilistic data structures in python http://pyprobables.readthedocs.io/en/latest/index.html
A probabilistic data structures library for C#
Count-Min Sketch Implementation in C
An implementation of Count-Min Sketch in Golang
A compressed adaptive optimizer for training large-scale deep learning models using PyTorch
PHP client for RedisBloom module
🎛️ Use RedisBloom in PHP!
High performance approximate algorithms in Go (e.g. morris counter, count min, etc.)
LFU-based in-memory cache in Rust
an implementation of Count-Min Sketch, an approximate counting data structure for summarizing data streams, in golang
Thread-safe and persistent Golang implementations of probabilistic data structures: Bloom Filter, Cuckoo Filter, HyperLogLog, Count-Min Sketch and Top-K
Implementation and experimental tests of various algorithms.
Spark with probabilistic algortighmts - Bloom filter, HLL, QTree and Count-min sketch
Repository for an article series on probabilistic data structures including Skiplist, bloom filter, counting bloom filter, count sketch, count min sketch etc
Some advanced data structures' implementations in C++
This repository contains a collection of three Data Engineering capstone projects made for the DTU Data Engineering course 02807: Computational Tools for Data Science
Repository for implementation details for Data-Science
The project aims to find the trend by extracting and analyzing top k words in real-time posts of Twitter.
PoC (Proof of Concept) caching optimization algorithm for graphical tree environment, written entirely in pure C++.
Collection of code covering various topics in Machine Learning