Machine Learning Engineer specialized in designing, training and deploying predictive models and production-ready ML systems. Strong experience in Python, data pipelines, model evaluation, and MLOps practices using Linux, Docker and CI/CD automation.
View GitHub ProjectsEnd-to-end data pipelines, feature engineering, model training, automation and API development.
Supervised and unsupervised learning, model evaluation, hyperparameter tuning and production deployment.
Dockerized ML services, CI/CD pipelines, model versioning and automated testing with GitHub Actions.
Production environments, performance optimization, monitoring and reproducible ML workflows.
RESTful APIs for model inference, integration with web services and scalable ML applications.
Strong analytical foundation supporting advanced modeling, optimization and data-driven decision making.
Sales Forecast ML is a time-series machine learning project that focuses on forecasting sales while preventing data leakage through proper temporal validation. The codebase provides utilities for feature engineering, model training, temporal cross-validation, evaluation, and interpretation.
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Unsupervised learning system for chronic patient segmentation and anomaly detection with advanced visualization and clustering analysis.
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End-to-end machine learning pipeline for breast cancer risk prediction, deployed as a REST API with Docker and automated CI/CD using GitHub Actions.
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