Projects using PyTorch in Rawalpindi
Projects using PyTorch in Rawalpindi
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$501 earned
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Usama Idrees
IT/AI Infrastructure Support
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54
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JUNAID Mohi Ud Din
Smart Farming Advisor — Agentic AI The Smart Farming Advisor is an end-to-end agentic AI system that empowers the agriculture sector with data-driven crop recommendations and accurate plant disease detection. Utilizing an intelligent agentic routing system for autonomous intent classification, the platform seamlessly integrates computer vision models (ResNet50) and machine learning classifiers (Random Forest). It features a comprehensive RAG pipeline with semantic search for farming Q&A, bridging a Next.js 14 frontend with a Flask REST API backend. This project emphasizes my ability to orchestrate multi-tool AI assistants and deliver high-impact predictive modeling solutions.
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34
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Arham Malik
Yeah, this one is a bit out there, but it was super fun. I built an AI that actually understands memes. It looks at the image and the text together using PyTorch, TensorFlow, and GPT 4. I used early and late fusion techniques to combine vision and language, plus Tesseract OCR to grab text from the image itself. The model hits over 95% accuracy on meme classification. It’s not your typical corporate project, but it shows how multimodal AI can understand humor, culture, and context. Definitely one of my favorite experiments. For more details, please visit: https://arham-nexus.vercel.app/work/memechecker
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75
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Fasih Ahmed
FasihCodes/Live-Poker-Game-Analysis-YOLOv8
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31
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Shaheer Zafar
Shaheerzafar5/News_Head-Line-Sarcasm-Detection
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5
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waqar ahmed
T5 Finetuning for SQuAD Question Answering
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8
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Touqeer Abbas
RAG based chatbot
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15
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Faraz Ahmad
Video surveillance for Shop lifting
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5
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Ammar Shah
Deployment of Large Language Model on Local Server
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4
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Muhammad Touseef
Brain Tumor Detection
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4
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Anas Awan
Explainable CNN Model for Remote Sensing
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6
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Haseeb Umer
Customer Segmentation Using Deep Learning Models
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3
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Umer Nazeer
Computer Vision Bag of Visual Words
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38
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Pervaiz Ahmad
Advanced Face Recognition System for Enhanced Security
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4
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JUNAID Mohi Ud Din
VisiHealth AI – Explainable Medical VQA VisiHealth AI is a multimodal, explainable Medical Visual Question Answering system designed to analyze complex clinical radiology scans. Utilizing PyTorch, ResNet-50, and BioLinkBERT, the platform fuses text and spatial image patches through a real multi-token cross-attention mechanism to provide accurate clinical insights. It builds diagnostic trust through explainable AI by overlaying attention-map heatmaps on original scans and deriving human-readable rationales from a 4,444-triplet medical knowledge graph. Delivered via a scalable Next.js and Flask architecture, it demonstrates my capability in deep learning and healthcare AI integrations
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Fasih Ahmed
Natural Language Processing with Disaster Tweets | Kaggle Compe…
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