Run Your Machine Learning Models as Dockerized Apps | ML Deployment with Docker

Описание: Tired of messy ML deployments? Learn how to package your machine learning models into Docker containers and deploy them like pros! In this project, we show you how to dockerize your ML model, make it portable, and run it anywhere — from local machines to the cloud.

📦 This is a must-watch for anyone looking to master ML model deployment, scalability, and production-readiness.

📊 What You’ll Learn in This Project:
✅ What is Docker & why use it for ML model deployment
✅ Step-by-step guide to create a Dockerfile for your ML project
✅ How to containerize and run your ML model as a microservice
✅ Exposing your model as a REST API using Flask + Docker
✅ Testing and scaling your containerized ML app
✅ Real-world ML deployment best practices

🎯 Who Should Watch This?
✔️ ML Engineers & Data Scientists ready to move beyond notebooks
✔️ Developers looking to package & ship models efficiently
✔️ Beginners wanting to learn ML deployment with Docker
✔️ Freelancers & AI startups building scalable AI products

🛠️ Tech Stack: Python, Scikit-learn / TensorFlow / PyTorch, Flask, Docker

🚀 Run, scale, and deploy your models with confidence!

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