End‑to‑End Sentiment Classification with FastAPI, DVC & Docker

Description

In this video, we build and deploy an end‑to‑end Sentiment Classification app using Python, scikit‑learn, and FastAPI. You’ll see the complete pipeline: data ingestion, preprocessing, feature engineering (Bag‑of‑Words vs TF‑IDF), model training (Logistic Regression), evaluation, and serving via a simple FastAPI UI. We also track experiments with DVC and containerize the app using Docker for easy deployment.