ML- Based Web App

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This is Dockerized- ML - Based Web App Created by Christofel Goenawan where the features are :

1. Machine Learning Model Created in Python in the Web
2. REST API to Use the Machine Learning Model
3. Contain Vary Machine Learning Models and Its Versions
4. A/B Testing Features for Models Development
5. Containerized Application in Docker
6. Simple Automatic Testing for Machine Learning Model and Pages

To create this Web- App User used Piotr Plonski's Paper as references.

The Web App is build using Python , Django , and Flask Programming Languages. The Machine Learning Models contained here are:

• Random Forest Classifier
• XGBoost Classifier
• K - Neighbors Classifier

In this Project Writer used Adult Income's Dataset as dataset.

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Requirements:

1. ( Optional ) Git Platform in Local PC to Pull and Update the Codes ( for Windows's User Git Must be Installed First )
2. Python Version 3.6 ( Don't Use Python 3.7 )
3. Docker Engine Installed ( for Windows's User Docker Must be Installed First )
4. Python Packages as Written in requirements.txt

Some Notes:

• The Web App Can be seen in Photos Folder.
• For more information kindly reach me through : christofel04@gmail.com