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Hi πŸ‘‹, I'm DINRAJ K DINESH

AI / Machine Learning Engineer β€’ Deep Learning Practitioner β€’ Full-Stack Developer

Building intelligent systems, scalable web applications, and ML-driven products.

dinraj910

πŸ’« About Me:

πŸŽ“ MCA Student from India
🧠 Strong focus on AI, Machine Learning & Deep Learning
πŸ§ͺ Hands-on with ANN, CNN, RNN, NLP, Computer Vision
🌐 Experienced in Full-Stack Development (React, Node, Django, Flask)
πŸ›‘οΈ Exploring Cybersecurity, OSINT, Kali Linux & Secure Systems
🧩 Interested in systems programming, embedded systems & low-level computing
πŸ“ˆ Career-focused on high-impact, resume-worthy, real-world projects


🧠 Key Projects

  • πŸ“© Spam SMS Classification (NLP + LSTM RNN)
    End-to-end NLP pipeline with text preprocessing, tokenization, LSTM-based sequence modeling, evaluation, and deployment-ready architecture using TensorFlow/Keras.

  • 😊 Sentiment Analysis using LSTM (NLP)
    Resume-grade sentiment analysis system with custom word-level tokenization and recurrent neural network modeling for real-world text classification.

  • 🚦 Traffic AI – Real-Time Vehicle Detection & Flow Analysis (YOLOv8)
    Real-time vehicle detection, tracking, and traffic flow analytics using YOLOv8 and ByteTrack with GPU-accelerated inference and CSV-based reporting.

  • 🏚️ Structural Damage Severity Assessment (CNN)
    Computer vision system that classifies building damage severity from images, designed for disaster response and infrastructure inspection.

  • πŸ›’ Retail Loss Prevention & Shelf Intelligence (YOLO)
    YOLO-based retail analytics system detecting product–person interactions, shelf stock conditions, and generating explainable loss-prevention insights.

  • 🧬 DermaAI – Skin Lesion Classification (CNN + ResNet)
    Medical imaging application that classifies skin lesions as benign or malignant with confidence scores using deep CNN architectures.

  • 🏭 Industrial Defect Inspection (CNN Autoencoder)
    Unsupervised anomaly detection system for industrial surface inspection using reconstruction-based CNN autoencoders with explainable heatmaps.

  • 🧠 Visual CNN Builder with Code Generation (Full-Stack ML)
    Full-stack ML engineering platform enabling visual, layer-by-layer CNN design with automatic deep learning code generation.


🌐 Socials:

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πŸ’» Tech Stack:

C C# C++ CSS3 HTML5 Java JavaScript Markdown PHP Python TypeScript AWS Azure Cloudflare Oracle Vercel .Net Anaconda Bootstrap Django Chart.js EJS Electron.js Expo Express.js FastAPI Flask JavaFX jQuery JWT Next JS NodeJS Nodemon OpenCV React React Native React Query React Router React Hook Form Redux Socket.io Streamlit Three js Vite Apache Nginx Gunicorn MicrosoftSQLServer MongoDB MySQL Postgres SQLite Prisma Keras Matplotlib NumPy Pandas PyTorch scikit-learn Scipy TensorFlow GitHub Git Docker

πŸ“Š GitHub Stats:



πŸ† GitHub Trophies

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πŸ” Top Contributed Repo


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