This project is built using FastAPI and follows a microservices architecture. It includes a Gateway Service, ML Service, Auth Service ,Notification Service

MLOps project using FastAPI, Docker, and Poetry to deploy machine learning models with CI/CD automation via GitHub Actions on AWS EC2.

fastAPI used microservice creation and ml model

A modern microservices architecture showcasing FastAPI, ML processing, authentication, and real-time notifications

Simple fastapi skeleton for a stateless microservice (application for ml models, optimization, ...)

SoilSense_FastApi_MLmodel is a FastAPI microservice that inspects soil images with an OpenCV-powered ML pipeline to spot nutrient deficiencies.

Intelligent multi-cloud auto-scaler for Docker Swarm with ML-based load prediction . Scales across AWS/Azure using 4 triggers. Built with Python + FastAPI microservices .

Python FastAPI microservice for ML-driven credit decisioning (hybrid model + rules).

A FastAPI-based microservice that creates an ML model and exposes an API to predict energy consumption

Real-time credit card fraud detection platform built with FastAPI microservices, XGBoost ML, Kafka streaming, and React dashboard.

Modified fastapi microservice with scheduled A/B tests of base&enhanced catboost models (microservice based on final project of Start ML course at karpov.courses)

A polyglot microservice application that automates pull‑request code reviews using ML‑driven linting and static analysis. Includes a Go gRPC backend, Python FastAPI ML service, React + TypeScript dashboard, Docker‑compose setup, and GitHub Actions CI.

A 20-week structured roadmap to become a backend-focused fullstack engineer using Nest.js, PostgreSQL, React, and TypeScript, with progressive integration of advanced backend tools, AI/ML microservices, and production-ready deployment practices. Includes projects, real-world features (OAuth, 2FA, WebSockets, Redis, Zod), AI/ML microservices FastAPI

Real-time fraud detection platform with XGBoost ML scoring, microservices architecture, WebSocket streaming, and compliance audit trails. Built with Spring Boot, Python FastAPI, React, PostgreSQL — fully containerized with Docker.

🚀 EcomOpti: 6-phase ML pipeline for telco churn prediction, CLV estimation & retention campaign optimization. Features survival analysis, causal uplift modeling, budget optimization, FastAPI microservice & interactive Power BI-style Dash dashboard.

Platform for finding similar products using image similarity. Built with Dockerized microservices: React frontend, FastAPI backend, BentoML ML service with CLIP model, Minio object storage, and Oracle database. Upload images to find visually similar products, with automated setup and orchestration via Docker Compose.

✅ Complete ML Pipeline: Intent Classifier + Risk Assessment Model ✅ Performance Targets Met: AUC > 92% (achieved 92.3%) ✅ FastAPI Microservice: RESTful API with validation ✅ Streamlit Dashboard: Clinical interface ✅ Docker & Kubernetes: Production deployment configs ✅ CI/CD Pipeline: GitHub Actions workflow

No description available

⚡ ML inference: FastAPI + Redis cache + Prometheus + JWT + HPA

No description available

No description available

This repo contains a full fledged ML based microservice. Utilizes the FastAPI framework for end point mapping. Deployed using AWS ECR and ECS.

No description available

ML microservice with FastAPI + Docker + CI

Develop & Dockerize ML Microservices using FastAPI + Docker

Scalable FastAPI microservices recommendation system with ML

AI-powered fraud detection microservice using FastAPI and ML

HealthSync+ ML Service - FastAPI microservice for AI predictions and OCR

Production-style ML microservice using FastAPI, PyTorch, PostgreSQL and Docker.

FastAPI microservice for image background removal using a lightweight ML model