Data Science Projects

This section showcases my machine learning and data analysis projects, demonstrating various techniques from exploratory data analysis to predictive modeling.

Diabetes Prediction Project

Objective: Develop a machine learning model to predict diabetes risk based on patient health metrics.

Technologies: Python, Scikit-learn, Pandas, NumPy, Matplotlib Key Techniques: Classification, Feature Engineering, Model Evaluation

Student Habits and Academic Performance

Objective: Analyze the relationship between student study habits and academic performance to identify key factors affecting educational outcomes.

Technologies: Python, Pandas, Seaborn, Statistical Analysis Key Techniques: Exploratory Data Analysis, Correlation Analysis, Data Visualization

🎯 Project Highlights

  • End-to-end ML pipeline development
  • Statistical analysis and hypothesis testing
  • Feature engineering and selection
  • Model performance evaluation and optimization
  • Data visualization and storytelling

📊 Skills Demonstrated

  • Data Preprocessing: Cleaning, transformation, and feature engineering
  • Machine Learning: Classification, regression, and model selection
  • Visualization: Creating compelling charts and graphs
  • Statistical Analysis: Hypothesis testing and correlation analysis
  • Python Programming: Advanced pandas, numpy, and scikit-learn usage

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