Popular GitHub Repositories for Kafka

PipelineAI

Metering and Billing for AI, API and DevOps. Collect and aggregate millions of usage events in real-time and enable usage-based billing.

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model architecture, and Kafka for real-time data streaming and pipelining.

LangStream. Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by Kubernetes and Kafka.

Real Time Big Data / IoT Machine Learning (Model Training and Inference) with HiveMQ (MQTT), TensorFlow IO and Apache Kafka - no additional data store like S3, HDFS or Spark required

? Open Source App Framework to build streaming apps with real-time data - ? Build real-time data pipelines and make real-time data universally accessible - ? Join historical and real-time data in the stream to create smarter ML and AI applications. - ? Standardize complex data ingestion and stream data to apps with pre-built connectors

Modular e-commerce backend with a GraphQL gateway and gRPC microservices for accounts, products, orders, and recommendations.

Kafka Streams + Java + gRPC + TensorFlow Serving => Stream Processing combined with RPC / Request-Response

Tangseng search engine including full text search and vector search base on golang. 基于go语言的搜索引擎，信息检索系统

Repo that relates to the Medium blog 'Keeping your ML model in shape with Kafka, Airflow' and?MLFlow'

Open source Mixpanel with AI

Machine learning around business processes

? Stream inferences of real-time ML models in production to any data lake (Experimental)

The purpose of this tiny project is to put things together with the know how that i learned from the course big data expert from formacionhadoop.com The idea is to show how to play with apache spark streaming, kafka,mongo, spark machine learning algorithms.

Full-stack Highly Scalable Cloud-native Machine Learning system for demand forecasting with realtime data streaming, inference, retraining loop, and more

Stream processing using kafka-python to track people (user input images of target) in the wild over multiple video streams.

Data Analysis Using Hadoop/Spark/Storm/ElasticSearch/MachineLearning etc. This is My Daily Notes/Code/Demo. Don't fork, Just star !

Slipstream提供了一种数据流模型，简化了有状态流式应用程序的开发。

Credit card fraud detection using kafka,scikit,flask,cassandra