Data Scientist | AI/ML Engineer | MLOps | Cloud Enthusiast (GCP, AWS & Heroku)
I solve business problems with data-driven insights and build scalable AI/ML solutions for real-world impact.
Languages & Tools I use
| Project | Description |
|---|---|
| Scalable-MLOps-Pipeline-for-Credit-Risk-Prediction | Built a full ML pipeline for credit risk: data ingestion, feature engineering, model training / evaluation. Integrated best practices in reproducibility and pipeline scaling. |
| Taxi-Fare-Prediction-with-BigQuery-ML | Used BigQuery ML to build regression models on a large dataset, optimized queries, and evaluated performance at scale. Strengthened cloud-native ML skills. |
| Boston-MEDV-House-Prediction | Regression project to predict housing prices. Worked on feature selection, model evaluation, and interpreting model outputs. |
| Telemarketing-Campaign-Prediction | Classification project analyzing bank telemarketing campaigns. Built predictive models to identify potential responders and improved understanding of customer behavior. |
| Feature-Engineering-with-Keras | Hands-on work with feature preprocessing and engineering for different data types using Keras / TensorFlow. Improved understanding of how features affect model performance. |
- Improving model deployment / CI/CD for MLOps projects
- More end-to-end projects with unstructured data (text, images)
- Deepening cloud skills (AWS/GCP) by combining pipelines + deployment
I’m always open to collaboration, mentorship, or exchanging ideas.
--> Check out the pinned repositories above, I’d be happy to walk you through any in detail!