🚀 Scaling ML Models with FastAPI, Docker, and Kubernetes: Practical Tutorial

Description

Take your Machine Learning model deployment to the next level! 🚀 In this hands-on tutorial, you’ll learn how to scale ML models using FastAPI, Docker, and Kubernetes — the ultimate MLOps stack for production-ready systems. Minikube Setup: https://youtu.be/CYfFzJDWnyI FastAPI + ML: https://youtu.be/le3tJIcXyaQ Github: https://github.com/Mayurji/Explore-Libraries/tree/main/FastAPI/deployment Here’s what you’ll learn: ✅ Serving ML models with FastAPI ✅ Containerizing your app using Docker ✅ Deploying and scaling with Kubernetes (K8s) ✅ Managing replicas, load balancing, and rolling updates ✅ Best practices for reliable and efficient ML deployments Whether you're an ML engineer or developer, this video gives you a complete guide to scalable ML model deployment — from local testing to cloud-ready Kubernetes clusters. 🔔 Subscribe for more MLOps, FastAPI, and Machine Learning Deployment tutorials! #FastAPI #Docker #Kubernetes #MLOps #MachineLearningDeployment #ModelServing #ScalableAI