vivek sharma
ML & MLOps Engineer | Python, FastAPI, Docker, AI
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Built a machine learning application that predicts house prices from property features such as area, number of bedrooms, and bathrooms.
The project includes data preparation, model training, prediction, model saving, and integration with a FastAPI REST API. The application was also containerized with Docker and tested locally through API requests.
This project demonstrates the complete workflow from machine learning model development to API-based prediction and containerized deployment.
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Built a customer churn prediction system using Python, Pandas, NumPy, and scikit-learn. The project covers data preprocessing, exploratory analysis, model training, evaluation, and prediction. The trained model was integrated with FastAPI and deployed in Docker, creating a complete ML-to-API workflow that was built and tested locally.
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Built a machine learning application that classifies messages as SPAM or HAM using Python and scikit-learn. The project includes text preprocessing, feature extraction, model training and evaluation, FastAPI API integration, Docker deployment, and Git/GitHub version control. The application was built and tested locally.
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Built an end-to-end fraud detection MLOps system covering machine learning, FastAPI deployment, Docker, MLflow, Airflow, and monitoring with Prometheus and Grafana. The complete workflow was built and tested locally.
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