Train → Deploy: Build Your First AI API with Python & FastAPI

Description

In this video, I walk you through the exact process a real AI Engineer follows — from training a machine learning model to serving it as a live REST API. What you'll learn: ✅ Train a sentiment analysis model with scikit-learn ✅ Save and load your model with joblib ✅ Wrap it in a production-ready API using FastAPI ✅ Test it with the built-in Swagger UI ✅ (Bonus) Containerize everything with Docker 🛠 Tools Used: - Python 3.10 - scikit-learn - FastAPI - Uvicorn - Docker (optional) This is the exact workflow used in real AI/ML engineering roles. No fluff. Just code. ⭐ Drop a comment if you want Part 2 — connecting this API to a React frontend! #Python #MachineLearning #FastAPI #AIEngineering #MLOps #ArtificialIntelligence #DataScience #Docker #APIDesign #PythonTutorial #LearnPython #ScikitLearn #BuildWithAI #MLEngineer #TechTutorial #Coding #Programming #DeepLearning