PROFESSIONAL SUMMARY
Artificial Intelligence and Data Science student with hands-on experience in Machine Learning, Deep Learning, Computer Vision, NLP, and building AI-powered applications, real-time analytics systems, and automation workflows. Proficient in Python, TensorFlow, Scikit-Learn, Pandas, NumPy, Flask, Streamlit, REST APIs, and model deployment on Hugging Face Spaces. Strong focus on delivering scalable, real-world AI solutions.
PROJECTS
ATLAS AI – F1 Telemetry Data Analysis and Visualization System
Technologies: Python, Plotly, Flask
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Built full-stack analytics dashboard using Python, Plotly, Flask to visualize F1 telemetry data for 20+ races
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Deployed interactive comparison tool serving 500+ motorsport enthusiasts
DermaScan AI – Deep Learning Project
Technologies: TensorFlow, EfficientNetB0, Haar Cascade, Hugging Face Spaces
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Developed end-to-end CNN pipeline using TensorFlow and EfficientNetB0 with 94% accuracy and 89% precision
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Trained on HAM10000 dataset (10,015 images) using transfer learning with Haar Cascade preprocessing
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Deployed on Hugging Face Spaces with inference time <2 seconds per image
Workflow Automation System using n8n
Technologies: n8n, REST APIs
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Designed automated workflows integrating multiple REST APIs for business process automation
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Reduced manual effort and enhanced operational efficiency through trigger-based systems
Stock Price Prediction using RNN & LSTM (NeuroTrade AI)
Technologies: LSTM, RNN, Time-Series Forecasting, Real-time APIs
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Developed a deep learning time-series forecasting system using LSTM and RNN architectures for NIFTY-50, leveraging real-time APIs to stream live stock data (Google, Apple, Tesla, etc.); achieved MAE of 2.3% and RMSE of 3.1%, with interactive trend visualization for decision support.