Stop Using Notebooks: How to Deploy ML Models with Docker

In this video, I walk through an End-to-End Machine Learning project where I take a model from a Jupyter Notebook and deploy it as a production-ready containerized API.

🚀 *Project Source Code:* https://github.com/aaronwillyOG/trend_detection_ml
🔗 *Connect on LinkedIn:* https://www.linkedin.com/in/aaron-willy/

*What I Built:*
A real-time Bitcoin trend detection system using:
- *Data:* Live financial data via yfinance
- *Model:* XGBoost Classifier (Trained on technical indicators)
- *Backend:* FastAPI (High-performance Async API)
- *Deployment:* Docker (Containerized for reproducibility)
- *Frontend:* Streamlit (Interactive Dashboard)

*Tech Stack:*
Python 3.10, Pandas, Scikit-Learn, XGBoost, Docker, FastAPI, Uvicorn.

#MachineLearning #MLOps #Docker #Python #Portfolio

Видео Stop Using Notebooks: How to Deploy ML Models with Docker канала Aaron Willy