Distributed stream processing engine in Rust
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Updated
Dec 3, 2024 - Rust
Distributed stream processing engine in Rust
Memphis.dev is a highly scalable and effortless data streaming platform
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
Online anomaly detection for data streams/ Real-time anomaly detection for time series data.
RTEC is an Event Calculus implementation optimised for stream reasoning
Golang app to read records from a set of kafka topics and write them to an elasticsearch cluster
Faust dockerized application
A real time Tweet Trend Map and Sentiment Analysis web application with kafka, Angular, Spring Boot, Flink, Elasticsearch, Kibana, Docker and Kubernetes deployed on the cloud
OscillatorIMP ecosystem for the digital characterization of ultrastable oscillators and Software Defined Radio (SDR) frontend processing
This repository includes code for the AutoML-based IDS and adversarial attack defense case studies presented in the paper "Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis" published in IEEE Transactions on Network and Service Management.
RealTime StockStream is a streamlined, simulation system for processing live stock market data. It uses Apache Kafka for data input, Apache Spark for data handling, and Apache Cassandra for data storage, making it a powerful yet easy-to-use tool for financial data analysis
Real-time Emotion Recognition using Physiological signals in e-Learning Here one can find the development of realtime emotion recognition using various physiological signals
This code belongs to ACL conference paper entitled as "An Online Semantic-enhanced Dirichlet Model for Short Text Stream Clustering"
Realtime Data Processing and Search Engine Implementation.
Flink Example
Apache Kafka for the Hybrid IoT
Real-time visual analytics for soccer matches, leveraging Apache Flink, Apache Kafka and the Elastic stack. Solution to DEBS 2013 Grand Challenge. Coursework in Systems and Architectures for Big Data 2016/2017.
Hybrid Forest: A Concept Drift Aware Data Stream Mining Algorithm
Real-time visual analytics application for link prediction and link detection in criminal networks. Research work accepted to the 5th IEEE International Conference on Future of Internet of Things and Cloud (FiCloud 2017).
Code examples for Chapter 7 of Data Wrangling with JavaScript
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