iQuantC/Scikit-learn-Streamlit-Docker-Kubernetes
In this step-by-step tutorial, learn how to build, visualize, and deploy a Scikit-learn machine learning model using Streamlit for the UI, Docker for containerization, and Kubernetes (Minikube) for scalable deployment!
This project helps developers build and deploy machine learning models with a web-based user interface. It takes a Scikit-learn model and outputs an interactive web application, containerized for easy deployment. Developers who need to showcase or make their ML models accessible to end-users without deep technical knowledge would use this.
No commits in the last 6 months.
Use this if you are a developer looking for a practical, step-by-step guide to take a Scikit-learn model from prototype to a scalable web application.
Not ideal if you are a non-technical user trying to build or use a machine learning model without programming or deployment knowledge.
Stars
6
Forks
4
Language
Python
License
MIT
Category
Last pushed
Jun 19, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/iQuantC/Scikit-learn-Streamlit-Docker-Kubernetes"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
yashasvini121/predictive-calc
An interactive web application developed with Streamlit, designed for making predictions using...
vsergeyev/loudml-grafana-app
Visualization panel and datasource for Grafana to connect with Loud ML AI solution for ICT and...
RihabFekii/streamlit-app
Streamlit and FastAPI app for water potability assessment
redcican/pycaret-streamlit
An End-to-End Machine Learning Web Application for Classification and Regression problem using...
flrs/build_and_test_ml_quickly
From idea to production in a day: Leveraging Azure ML and Streamlit to build and user test...