Build & Deploy a Machine Learning Model using FastAPI | Beginner to Advanced

In this video, you will learn how to Build and Deploy a Machine Learning Model using FastAPI step by step.

This tutorial covers:
✔️ Machine Learning Model Creation
✔️ Saving & Loading Models using Pickle
✔️ Building REST APIs with FastAPI
✔️ API Testing using Swagger UI & Postman
✔️ Running FastAPI Server
✔️ Real-Time Prediction API
✔️ Complete End-to-End ML Deployment Project
commands: pip install fastapi uvicorn python-multipart pandas numpy scikit-learn joblib
code link: https://github.com/erirfan04/GenAI_Example_usingPython
Whether you are a Beginner, Python Developer, Data Scientist, or AI Engineer, this video will help you understand how to deploy ML models in real-world applications.

🔥 Technologies Used:

Python
FastAPI
Scikit-learn
Pandas
NumPy
Uvicorn
Pickle

📌 Perfect for:

Machine Learning Beginners
AI Engineers
Python Developers
Data Science Students
FastAPI Learners

👉 Don’t forget to Like, Share, and Subscribe for more AI & Machine Learning tutorials!

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Видео Build & Deploy a Machine Learning Model using FastAPI | Beginner to Advanced канала ElevateMyCode