Highly passionate AI & MLOps Engineer skilled in building scalable ML solutions, cloud deployments, and end-to-end automation using FastAPI, Docker, AWS, and CI/CD.
Experienced in developing intelligent applications, MLOps pipelines, and real-world AI solutions with strong foundations in Python, data science, and cloud platforms.
- Machine Learning: Regression, Classification, Random Forest, SVM, Gradient Boosting
- MLOps & Deployment: Docker, GitHub Actions, CI/CD, FastAPI, Streamlit, AWS EC2, S3
- Data Engineering: ETL, EDA, Feature Engineering, Data Visualization
- Cloud Platforms: AWS EC2, S3, VPC, IAM
- DevOps Tools: Docker, Git, GitHub, GitHub Actions, FastAPI, Streamlit
- Programming & Tools: Python, MySQL, NumPy, Pandas, Matplotlib, Seaborn
🔹 Built predictive models to detect Parkinson’s, Heart, Lung, and Thyroid diseases using SVM & Logistic Regression.
🔹 Deployed using Streamlit for real-time interactive predictions.
🔹 Implemented hyperparameter tuning and improved classification performance.
🔹 Designed an end-to-end IDS pipeline using ML to detect cyber threats from network data.
🔹 Integrated Docker, GitHub Actions, AWS EC2, and FastAPI for automated deployment.
🔹 Achieved high detection accuracy with Random Forest and Gradient Boosting.
🔹 Built Flask web application for used car price prediction.
🔹 Applied Random Forest & Linear Regression for accurate price estimation.
🔹 Used Matplotlib & Seaborn for data visualization and feature correlation.
- B.Tech in Computer Science & Engineering – TCTK, Karimnagar (2020–2024)
📊 CGPA: 6.90
🔍 “Driven by innovation, powered by data, and deployed to the cloud.”