https://github.com/sudo-xda/ai-deployment-workflow

This repository provides a beginner-friendly end-to-end Machine Learning project . The project demonstrates how to: ✅ Train and pickle a Machine Learning model 📊 ✅ Build a Flask API to serve predictions 🌐 ✅ Use Jinja2 templates to create a simple web interface 🖥️ ✅ Deploy and integrate an ML model into a real-world application 🚀
https://github.com/sudo-xda/ai-deployment-workflow

Last synced: about 1 month ago
JSON representation

This repository provides a beginner-friendly end-to-end Machine Learning project . The project demonstrates how to: ✅ Train and pickle a Machine Learning model 📊 ✅ Build a Flask API to serve predictions 🌐 ✅ Use Jinja2 templates to create a simple web interface 🖥️ ✅ Deploy and integrate an ML model into a real-world application 🚀

• Host: GitHub
• URL: https://github.com/sudo-xda/ai-deployment-workflow
• Owner: sudo-xda
• Created: 2025-03-17T06:56:32.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-17T10:39:38.000Z (over 1 year ago)
• Last Synced: 2025-03-17T11:34:48.123Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 423 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# AI-Deployment-workflow

 This repository provides a beginner-friendly end-to-end Machine Learning project . The project demonstrates how to:  ✅ Train and pickle a Machine Learning model 📊 ✅ Build a Flask API to serve predictions 🌐 ✅ Use Jinja2 templates to create a simple web interface 🖥️ ✅ Deploy and integrate an ML model into a real-world application 🚀