Cross-platform, customizable ML solutions for live and streaming media.
- mediapipe
- c-plus-plus
- computer-vision
- deep-learning
Repository Index
47,133 repositories indexed
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Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
- kafka
- cpp
- kubernetes
- go
ZeroMQ core engine in C++, implements ZMTP/3.1
- zeromq
- zmq
- messaging
- concurrency
A modern high-performance open source message queuing system
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
- clickhouse
- kakfa
- sql
- redpanda
Eclipse iceoryx™ - true zero-copy inter-process-communication
- iceoryx
- eclipse
- ipc
- inter-process-communication
Tenzir is the data pipeline engine for security teams.
- incident-response
- threathunting
- siem
- soc
The repository host gives no description.
- hacktoberfest
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
- data-analytics
- data-cleaning
- data-cleansing
- data-engineering
Distributed C++ services from embedded to enterprise
An effort to bring Google's Firebase C++ API to Qt + QML
Daggy - Data Aggregation Utility and C/C++ developer library for data streams catching
- serverless-framework
- streaming
- stream-processing
- qt
Data management for the sensor-edge-cloud continuum
- bigdata
- streamprocessing
Multi-core Window-Based Stream Processing Engine
- llvm
- incremental-computation
- aggregation
- stream-processing
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
- svm
- regression
- classification
- machine-learning