I'm passionate about solving real-world problems using AI/ML and data science. With a strong foundation in algorithms and deep learning, I aim to build scalable solutions that bridge technology and practical applications—from scientific computing at DRDO to optimizing inventory management with ML.
Frameworks & Libraries:
NumPy | Pandas | Scikit-learn | OpenCV | Streamlit | PyGame | Seaborn
Relevant Coursework:
Machine Learning | Deep Learning | Data Structures | DBMS | OOPs
🔬 Scientific Computing Intern | DRDO, Jodhpur (May 2024 - July 2024)
- Leveraged Python (Spyder IDE) for data analysis using NumPy, Pandas, and Matplotlib.
- Applied statistical methods to enhance computational tasks.
💻 Software Developer Intern | Kadam Technologies
- Built interactive web apps with Streamlit and automated tasks using Python bots.
- Designed a Bi-LSTM model with DBSCAN clustering for geometric shape recognition.
- Achieved adaptive learning using Recursive Backtracking.
- Boosted Random Forest model accuracy from 27% to 90% via hyperparameter tuning.
- Implemented custom Keras callbacks and ImageDataGenerator for 95% F1-score.
- � Top 5% in Adobe GenSolve (1L+ participants).
- 🚀 Top 374 in [Woodpecker’s Hackathon] (12K+ participants).
- ⭐ 600+ LeetCode problems solved (Profile).
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