https://github.com/ahmed-maher77/diabetes-prediction-app-using-machine-learning
Diabetes Prediction: Using machine learning to classify individuals as diabetic or non-diabetic based on health data, enabling early intervention and improved healthcare outcomes.
https://github.com/ahmed-maher77/diabetes-prediction-app-using-machine-learning
ai css data-science gradientboostinclassifier javascript logisticregression machine-learning matplotlib numpy pandas python randomforestclassifier seaborn streamlit supportvectormachine webdevelopment
Last synced: about 2 months ago
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Diabetes Prediction: Using machine learning to classify individuals as diabetic or non-diabetic based on health data, enabling early intervention and improved healthcare outcomes.
- Host: GitHub
- URL: https://github.com/ahmed-maher77/diabetes-prediction-app-using-machine-learning
- Owner: Ahmed-Maher77
- Created: 2024-04-12T19:06:31.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-21T00:34:09.000Z (12 months ago)
- Last Synced: 2025-01-24T06:45:39.154Z (3 months ago)
- Topics: ai, css, data-science, gradientboostinclassifier, javascript, logisticregression, machine-learning, matplotlib, numpy, pandas, python, randomforestclassifier, seaborn, streamlit, supportvectormachine, webdevelopment
- Language: CSS
- Homepage:
- Size: 396 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Diabetes-Prediction-using-Machine-Learning
Diabetes is a chronic health condition affecting millions worldwide. Early detection and management are crucial for preventing complications and improving patient outcomes. This project leverages the power of machine learning to predict the likelihood of diabetes in individuals based on various health parameters such as glucose levels, BMI, age, and more.
Using a dataset containing historical patient information, advanced machine learning algorithms are trained to analyze patterns and identify predictive features associated with diabetes. The resulting model can accurately classify individuals into diabetic or non-diabetic categories, providing valuable insights for healthcare practitioners and empowering individuals to take proactive measures for their health.
By harnessing the capabilities of machine learning, this project aims to enhance diabetes diagnosis, facilitate early intervention, and ultimately contribute to better healthcare outcomes for individuals at risk of this prevalent disease.
➲ **Used Technologies:**
Python - Streamlit - JavaScript - CSS - Python Libraries (pandas - numpy - matplotlib - seaborn - sklearn) - ML Algorithms (Logistic Regression - Support Vector Machine - Random Forest Classifier - Gradient Boosting Classifier)
➲ **Notebook (ML Code):** kaggle.com/code/ahmedmaheralgohary/diabetes-prediction