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Breast Cancer Prediction Web App | Machine Learning with Python & Streamlit

Early detection is critical in the fight against breast cancer. In this video, I walk through a machine learning-based Breast Cancer Prediction Web App developed using Python, Streamlit, and Scikit-learn.

What this app does:
This tool predicts the likelihood of breast cancer using essential diagnostic features, supporting early screening and potential intervention.

Technical Overview:

Dataset: Cleaned and preprocessed dataset with over 30 diagnostic features

Algorithms: Supervised learning models including Logistic Regression and Random Forest

Performance: Tuned for high accuracy and precision

Deployment: Built with Streamlit for a seamless, interactive user experience

Purpose of the Project:
Breast cancer impacts millions globally. This project was developed to support awareness and leverage AI for proactive, accessible health diagnostics.

Tools & Libraries Used:

Python

Scikit-learn

Streamlit

Pandas, NumPy, Matplotlib (for EDA & visualization)
source code availaible on @gitvedhub