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PreProd Corp
Data Analyst Intern
- Designed and implemented an end-to-end MLOps pipeline using Kafka, DVC, MLflow, PySpark and Scikit-Learn for a Food Demand Forecasting project [Nov '23 – Feb '24]
- Contributed to PreProdCorp's Opensrc' initiative by developing demo projects using tools like PySpark, RAG, GAN, MobileNet, Redis, and CouchDB [Mar '24 – Jul '24]
- Designed, organized, and executed the 2-day "Buildathon" Hackathon at VIT Bhopal; developed the MVP for the AutoML app demo, mentored participants, and assisted in evaluating final submissions [Aug '24]
- Led 20 interns across 6 teams as Team Leader, guiding the development of 30+ demo projects under the PreProdCorp Opensrc' initiative using PySpark, Pandas, Polars, CV, RAG, and GANs [Aug '24 – Jan '25]
- Acted as Scrum Master, conducting sprint meetings, ensuring timely delivery, and promoting MLOps best practices [Aug '24 – Jan '25]
technical skills
Python
NumPy
Pandas
Scikit-learn
TensorFlow
Docker
Redis
Scrum
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featured projects
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Food Demand Forecasting
Time-series model to forecast food demand with high accuracy. Implemented MLOps pipeline to enhance efficiency. Improved prediction accuracy, optimizing inventory management and reducing food wastage.
DVC
Flask
Kafka
MLFlow
Scikit-Learn
Calpred
Calorie prediction framework to estimate caloric expenditure from workout data. Features real-time tracking, interactive visualization, and data-driven fitness insights.
Dash
Flask
NumPy
Pandas
Plotly
SQLite3
TPOT
XGBoost