Pranjal K
AI/ML Engineer building RAG, GenAI & Python solutions
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Built a RAG-based document intelligence application that transforms uploaded documents into searchable knowledge for contextual question answering. Developed a FastAPI backend with PDF text extraction, recursive text chunking, SentenceTransformer embeddings, and semantic retrieval. The project demonstrates the core architecture behind document Q&A systems and AI knowledge assistants, with a modular Python backend designed for further development and integration.
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Built an object-detection pipeline for real-world road scenes using the KITTI dataset and Ultralytics YOLO11n. I developed dataset preparation, model training, validation, and inference workflows for detecting vehicles, pedestrians, cyclists, and other road objects. I evaluated performance using precision, recall, mAP, and CPU inference speed, exploring the practical trade-off between detection accuracy and latency on resource-constrained hardware.
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Built an AI-powered market analysis application with a Python and FastAPI backend. I designed structured API endpoints and modular workflows that combine market data analysis with AI-assisted interpretation and forecasting. The project demonstrates how AI, data processing, and backend APIs can work together to create an accessible decision-support tool for analyzing financial markets.
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https://github.com/Pranjal3002/SentinelAI.git
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