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May 1, 2020
Build a Machine Learning Web App with Streamlit and Python
Interactive ML web app enabling dataset upload, model comparison, and rapid experimentation from a browser interface.
Delivered a practical no-code/low-code interface for experimenting with classification models and feature workflows.
PythonStreamlitscikit-learn
Overview
Designed a lightweight ML app where users can upload data, train models, and compare results interactively.
Focus
- Model experimentation with SVM, Logistic Regression, and Random Forest
- Feature preparation and quick iteration workflows
- User-friendly interface for non-specialist experimentation
Project Link
Coursera Verification: https://www.coursera.org/account/accomplishments/verify/6ME4VCS5NZVD