Hi I’m Vridhi 👋
Learning to build practical data, analytics, and machine learning systems.
I work with data and machine learning, and I enjoy building things that don’t stop at analysis or models but are actually usable in practice. My work focuses on practical, reproducible solutions — understanding not just what works, but how those systems can be maintained and used in real settings.
I have worked with financial and operational datasets where data quality and consistency mattered as much as the insights themselves. Most projects here reflect learning-by-doing across forecasting, machine learning systems, computer vision, and deployment.
- Time-series forecasting projects and demand modeling
- End-to-end ML pipelines, APIs, and model monitoring
- Deep learning for object detection and image classification
- Knowledge-graph–based system modeling and structured data representations
- Building reliable data and ML pipelines that move beyond notebooks
- Applying machine learning and statistical analysis to real-world decision problems
- Exploring LLM and retrieval systems for structured knowledge applications
- Productionizing forecasting models with robust data validation and CI/CD
- Improving interpretability and operational reliability of ML systems
- Prototyping multi-modal approaches that combine vision and structured time-series data
- Languages: Python, SQL
- ML: PyTorch, scikit-learn, TensorFlow
- Infrastructure: Docker, FastAPI, Airflow, AWS/GCP
- Data: Pandas, Dask, data validation tools
I enjoy movies and music, and I like noticing patterns and structure in both — whether it’s a story, a dataset, or a system.
- Email: vridhi99@gmail.com