I am a results-driven and detail-oriented Data Science and AI enthusiast with a strong foundation in machine learning, deep learning, data analysis, and statistical modeling.
Proficient in Python and experienced with essential libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, TensorFlow, and more.
I specialize in building end-to-end AI/ML solutions — from data preprocessing and model development to deployment.
Passionate about continuous learning and applying AI to solve meaningful real-world problems, especially in healthcare and predictive analytics.
- Machine Learning & Deep Learning for Healthcare and Diagnosis Assistance
- Data Analysis, Visualization & Statistical Modeling
- Predictive Modeling & Classification Algorithms
- End-to-End AI/ML pipeline development
- Proficient in Python, SQL, and C++ programming
- Experienced with ML frameworks and tools like TensorFlow, Scikit-Learn, Streamlit, Django, FastAPI
| Project Name | Description | Tech Stack | Link |
|---|---|---|---|
| Medical Diagnosis Assistant | Developed a desktop/web app integrating multiple ML models (Random Forest, Logistic Regression, Decision Tree) for disease, heart disease, and diabetes prediction. Real-time predictions with interactive Streamlit GUI and automated PDF report generation. Achieved accuracy: 97% (disease), 88% (heart), 90% (diabetes). | Python, Streamlit, Scikit-learn, Joblib, ReportLab | GitHub Repo |
| Multi-Model Comparison | Trained and evaluated Logistic Regression, Random Forest, Decision Tree, SVM, and KNN on a classification dataset. Hyperparameter tuning with GridSearchCV and performance visualizations through confusion matrices, ROC curves, and dashboards. | Python, Scikit-learn, Matplotlib, Seaborn | GitHub Repo |
| Future Weather Prediction | Built ML models to forecast temperature, humidity, and wind speed using historical data. Models include Linear Regression, Random Forest, XGBoost with evaluation metrics RMSE, MAE, and R². Created Streamlit UI for input and visualization. | Python, Scikit-learn, XGBoost, Streamlit, Matplotlib | GitHub Repo |
Thanks for visiting my profile! Feel free to connect and collaborate. 😊