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Diabetes Prediction Using Machine Learning
Developed a machine learning project to predict the likelihood of diabetes based on patient health-related input features.
The project involved preparing the dataset, performing data cleaning and preprocessing, analyzing the input features, training machine learning models, and evaluating model performance.
Key work:
Cleaned and preprocessed the dataset
Performed exploratory data analysis
Analyzed relationships between health-related features
Prepared features for machine learning
Trained and evaluated classification models
Built a simple Streamlit interface for prediction
Tools & Technologies: Python, Pandas, NumPy, Scikit-learn, Streamlit, Data Cleaning, Exploratory Data Analysis, Machine Learning
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