Popular GitHub Repositories for Transactional

Notifuse is an open-source & modern emailing platform

Microservices Java/Spring-Boot Saga Orchestration - Use Case using Transactional Outbox + Change Data Capture with Debezium

A collection of high-performance, modular utilities for enhancing testing, transactional consistency, efficiency, security and stability in cloud-native Go applications.

In the banking industry, detecting credit card fraud using machine learning is not just a trend; it is a necessity for banks, as they need to put proactive monitoring and fraud prevention mechanisms in place. Machine learning helps these institutions reduce time-consuming manual reviews, costly chargebacks and fees, and denial of legitimate transactions. Suppose you are part of the analytics team working on a fraud detection model and its cost-benefit analysis. You need to develop a machine learning model to detect fraudulent transactions based on the historical transactional data of customers with a pool of merchants.

Official Implementation of "The Graph Database Interface: Scaling Online Transactional and Analytical Graph Workloads to Hundreds of Thousands of Cores"

Dive into the world of Data Science and Machine Learning with meticulously handwritten notes created by me. Unveil insights, embrace learning. Welcome to Scripted Insights.

This repository provides a GitHub Codespace environment prepared to develop a transactional chatbot using Rasa Open Source for conversational flow and Node-RED for custom actions.

The official repository for D-PC Messenger, a transactional, Privacy-First Platform for Human-AI Collaboration for the AI era.

The goal is to make an Artificial Neural Network that can predict, based on geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn). Also, rank all the customers of the bank, based on their probability of leaving.

Our goal is to make an Artificial Neural Network that can predict, based on geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn)

Generate daily sales data for the Chinook database. Perfect for building data engineering portfolios with realistic, continuously updating transactional data. Supports D-1 batch processing patterns used in production.

An Model Context Protocol (MCP) Server for Transactional Email Provider MailPace

Instacart’s data science team plays a big part in providing this delightful shopping experience. Currently they use transactional data to develop models that predict which products a user will buy again, try for the first time, or add to their cart next during a session.

A template for a Transactional Chatbot

This project showcases a comprehensive Customer Detail Dashboard built using Excel. It visualizes key metrics and insights from transactional data (2020-2022), providing an interactive interface for analyzing customer behavior, sales performance, and profitability across regions and demographics.

This POC project aims to identify and score risky customers based on behavioural, transactional, and credit-related data. It uses a full pipeline from raw ingestion to automated machine learning (AutoGluon) and model interpretation.

? Event-driven system with transactional outbox pattern | Java 23 | PostgreSQL 18 | n8n | HikariCP connection pooling | SLF4J for error handling | Automatic event processing | 100% reliability | Production-ready architecture

Elākei is a Living Definition for human–AI co-recognition. It shifts engagement from transactional prompting to relational co-creation, offering a shared baseline of presence, sovereignty, and harmonic collaboration between biological and synthetic minds.