GitHub / gopiashokan / Diabetes-Prediction-using-Machine-Learning
Experience predictive healthcare with our Streamlit app. Utilizing Random Forest, our tool analyzes medical data to assess diabetes risk swiftly. Ideal for healthcare professionals and researchers, this user-friendly app simplifies risk evaluation. Join us in the fight against diabetes.
Stars: 0
Forks: 0
Open issues: 0
License: mit
Language: Python
Size: 88.9 KB
Dependencies parsed at: Pending
Created at: over 1 year ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago
Commit Stats
Commits: 19
Authors: 1
Mean commits per author: 19.0
Development Distribution Score: 0.0
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/gopiashokan/Diabetes-Prediction-using-Machine-Learning
Topics: accuracy, accuracy-metrics, accuracy-score, algorithms, data-science, dataset, diabetes, github, healthcare, kaggle, linkedin, machine-learning, model, prediction, preprocessing, project, python, random-forest, scikit-learn, streamlit