Saraswathi Kondapalli

Developed a Tableau dashboard to visualize key business metrics and trends.

Applied Excel-based data classification techniques to uncover actionable business insights.

Interpreted analytical findings to simulate real-world business decision-making processes.

Streamlined healthcare data extraction and transformation using Python and SQL, generating clean, structured datasets for efficient model development.

Engineered and deployed predictive models with scikit-learn and TensorFlow (SVM, logistic regression, random forest), boosting diagnostic accuracy by 18%.

Optimized model performance by executing robust feature engineering and data preprocessing pipelines, significantly improving precision, recall, and F1 scores.

Deployed interactive Machine Learning solutions via Streamlit, reducing stakeholder validation time by 40% and enhancing user feedback collection.

Implemented end-to-end data preprocessing pipelines using Python, Pandas, and NumPy, ensuring high-quality datasets for robust model training.

Developed and optimized machine learning models (SVM, logistic regression, random forest), increasing predictive accuracy by 15% on test datasets.

Conducted rigorous model evaluation and hyperparameter tuning, optimizing performance metrics (precision, recall) and significantly reducing model error rates.

Presented clear, data-driven insights to technical and non-technical stakeholders, facilitating informed strategy development and project alignment.