Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

c++ LINQ -like library of higher-order functions for data manipulation

Estimating k-mer coverage histogram of genomics data

t-digest module for Redis

Performant implementations of various streaming algorithms, including Count–min sketch, Top k, HyperLogLog, Reservoir sampling.

Streaming operations on NumPy arrays

A Set of Streaming Algorithms in C++, Python, and Go

This is the codebase for Faucet, described in our manuscript: https://academic.oup.com/bioinformatics/article/34/1/147/4004871, by Roye Rozov, Gil Goldshlager, Eran Halperin, and Ron Shamir

Streaming, Memory-Limited, r-truncated SVD Revisited!

Federated Principal Component Analysis Revisited!

Create MPEG2-TS encapsulated stream-segments.

An online statistics library, written in Go

Automatic Keyword/Keyphrase Extraction from Text Streams

DynoGraph benchmark suite, implemented using the STINGER graph engine

CoEuS: Community Detection via Seed-set Expansion on Graph Streams

Simulates a HTTP Adaptive Streaming (HAS) session based on a throughput pattern and video segment sizes.

Approximation streaming algorithms, written in Go

Profile. Generate data profiles in the browser (work in progress)

Algorithms developed while attending the Foundations of Data Science course @ RWTH-Aachen

A set of links and repos for modern online random forests

DiCeS: Distributed Community Detection Over Streams

An implementation of the Greenwald-Khanna approximate quantile streaming algorithm as a Spark user-defined aggregate function.