{"data":{"featured":{"edges":[{"node":{"frontmatter":{"title":"CODEPRO — AI Plagiarism Detection","cover":{"childImageSharp":{"gatsbyImageData":{"layout":"constrained","placeholder":{"fallback":"data:image/png;base64,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"},"images":{"fallback":{"src":"/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/30f07/codepro.jpg","srcSet":"/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/41624/codepro.jpg 160w,\n/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/1b894/codepro.jpg 320w,\n/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/30f07/codepro.jpg 640w","sizes":"(min-width: 640px) 640px, 100vw"},"sources":[{"srcSet":"/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/6de5b/codepro.avif 160w,\n/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/20389/codepro.avif 320w,\n/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/8c32c/codepro.avif 640w","type":"image/avif","sizes":"(min-width: 640px) 640px, 100vw"},{"srcSet":"/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/60b4d/codepro.webp 160w,\n/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/5e011/codepro.webp 320w,\n/PORTFOLIO_NEW_IMPROVED/static/c7a104ef1505da3308a6b30bdadf4763/90d07/codepro.webp 640w","type":"image/webp","sizes":"(min-width: 640px) 640px, 100vw"}]},"width":700,"height":700}}},"tech":["Python","Winnowing Algorithm","Rabin-Karp Hashing","FastAPI","Streamlit"],"github":"https://github.com/Vinay0905/Plagarism_CODEPRO","external":"","cta":""},"html":"<p>A modular, end-to-end code plagiarism detection system that goes beyond simple text matching. Implements the Winnowing algorithm with k-gram fingerprinting and Rabin-Karp rolling hashes to accurately detect copied code. Features a robust normalization pipeline to catch variable renaming, whitespace changes, and comment removal — the tricks students typically use to evade naive detectors.</p>"}},{"node":{"frontmatter":{"title":"Regression-ML-EndtoEnd","cover":{"childImageSharp":{"gatsbyImageData":{"layout":"constrained","placeholder":{"fallback":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAIAAAAC64paAAAACXBIWXMAAAsTAAALEwEAmpwYAAAD2klEQVQ4y13SWW8aVxgG4G/2DcwMy4BZZ2BsDLjG4Jlh2GYw+07ArMZ2rNhJrdZpKkVylIu6itKrSs0vaP9rNSiqkkqPXp3znu/o3BwApwLOhJ0OBZwK8tXBjoI4E8h3pQKOhD3pUIA7AODiwMp2OhVg40BLwMg29pu0SUDtjpwKcAm7Z+OAuZK4O40JKeCPnMmKaPS8Ri9gjUVzLFovPKWB35r4KkOxNAhURvxxDVxHKJ+yr7gOAfceE4Esvp/DYjqvdUO9ta/6Yr+5EBtzf3vprc/E5lysX4jWNNzfuI0BEjoj9nNE4BT3pAFzp6moKqpdr9oVjSFxaEJIBdlwlUZCdcxXhnx5hMgGhFWIanyuGWrO+Nw5Ecnh7hTQMZ1SSnSiKNQmXLZJpBvkWZ/Whoza9Vzd+396x+g9UhuSuY6jMnW3V0JrsVccsLlzWtKAlAx0/5TONAKvPzjrKzRZosoTqjxkm+vAb3/uf/7CNDdkZUzXpvzwxnf33r147V0+OLQuKetAKEVc1vF4zWlds8acyDWZ9pKwJqS14rdP/OUTaS7J8ynbW7P1te/VEz+75/u3XL6DR/KAyRqeMOiM6R0vab1DFLrMYEX3Nq7tL66rn/euH13rd+zkhpteUaX53vjBNbjlzQ2T7WDSGWDxApU1hfoq9PK90LtkahP3w6/c8p7pveFWj9zyLdv5kZvf7d28IfU+Z84801doUCWSZUzW7JcZtY7GCo7yDEtbdG3sunskeyuqs/B//EP8+Jlsz4nOkpnforkGmW876xsInOKHRSyuAZ4wqFSFLXTDH56F2UvaGjGjLdVdiW+fpS9/S3/943t4pgeXzOgKDitsdeye3YLvBI8XMEkFIm4QMZXJ9/3bT87WLZ4953pbojYjq1vP5nfP+hNhXpO1GdtZI0qZyvddrTtCKuORMyKmAp0oosH8Xtw47l8H9AHEdMa8EBpL0Zq4zblgLhx612HOyMpsL9dKdRYHtelBdcwdlMlEEchgnk5WPYVeqHXhq46pkzap94Xzhdhe040p3bzwtla8NSO1AXXaCbbm4fHGq3eYI5PYPwVMSFFRDZcLWLKMH1WJtIWnqyAXQSkhGQvJWKCUkUSRyFh4qoalLTxVxWWdDOcxIQm4O03481REJ4MqFS9hERWNakhUsz9zWIWIDYlqaERFg3kqXqRCKhUzCP8pLqQA5RTMeYgKKcx7jLjT4NnxHYP/BPFnEf8JiCfg+wE8GfBkEHcG9WRQ/si+wikAXAzYKLCSjZOAkxGHBDYZ2QFbfJd2ac/Y81F7AZy8I30j9v32v/J/fexfi0S2kNKgz5oAAAAASUVORK5CYII="},"images":{"fallback":{"src":"/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/30f07/mlops.jpg","srcSet":"/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/41624/mlops.jpg 160w,\n/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/1b894/mlops.jpg 320w,\n/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/30f07/mlops.jpg 640w","sizes":"(min-width: 640px) 640px, 100vw"},"sources":[{"srcSet":"/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/6de5b/mlops.avif 160w,\n/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/20389/mlops.avif 320w,\n/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/8c32c/mlops.avif 640w","type":"image/avif","sizes":"(min-width: 640px) 640px, 100vw"},{"srcSet":"/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/60b4d/mlops.webp 160w,\n/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/5e011/mlops.webp 320w,\n/PORTFOLIO_NEW_IMPROVED/static/9015ade58e3ef266baa4164c753ebdc7/90d07/mlops.webp 640w","type":"image/webp","sizes":"(min-width: 640px) 640px, 100vw"}]},"width":700,"height":700}}},"tech":["Python","XGBoost","Optuna","FastAPI","GCP Cloud Run","Supabase"],"github":"https://github.com/Vinay0905/Regression_ML_EndtoEnd","external":"","cta":""},"html":"<p>A production-grade, end-to-end MLOps pipeline designed for real-world regression tasks. Features a modular architecture for automated feature engineering, XGBoost model training, and hyperparameter tuning via Optuna. The trained model is containerized and deployed as a FastAPI service on Google Cloud Run, with Supabase used for persistent prediction storage and experiment tracking.</p>"}},{"node":{"frontmatter":{"title":"Fish Detection — YOLOv8","cover":{"childImageSharp":{"gatsbyImageData":{"layout":"constrained","placeholder":{"fallback":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAIAAAAC64paAAAACXBIWXMAAAsTAAALEwEAmpwYAAAERUlEQVQ4yx3L2W/adhwA8O/PxsYHEK4QThswRwCbw+Y0NxhsgsORgwaagyZpl3ZTeqybOq27q07r09T3TZpUaY973L83aZ/3D0A0h2IKxCqQbIDYg9IIygaUJ1A5QI0ZahyiioEpOipqqDAEsYuKQ6xsQKIM0SIAl4OoUioPzO5BpXVAyzpdndL1GdM6sjQW0JgjdYEah3hzhtV0S2tiNWbkUMcyIpZTAMI5Ml4+Vofb0XwyPg61DkPjTXD4kOus+N4Ka6/wzgo6K3K6oQ0zvl5f/vbOf/0UpsdYXvw/84o3LEJIQqUh9JZgrK0Xz5j5Fd9f0do5GmycVy8v//yUvP1i/vNPH//9J/BgC2INF2sAoey8pX+rT0dNw5nvsfLQWdfd+jJorvjeEQzX2NHjzPvfl398ynz+lXx1nTh9YDFOUHQfE+tARyW93Jt2jEF/VmyZxboZqpnBhhlS557+MTpYU9t7x8vvd87vuJMzrz7JX97ETi4gGMeCSaDD+4F4AeJFEFWn0gvIYyiOkGJAc4q6C9DOYHYDyyf21WPv/KF9vHz619/qy7cgKIgTAfOnfVw2nJS5Qnuv2HEU+nRJw5URqk2s40XsxSb5zcPIm88cz78jj66i928qv360duYglCGUAeTlwZdAvAipijdbNxrDgarlVA0qulWbpb7eZH94Iv7yPHT7aO/2Mf/qy+Dd1lIdQrSA/CkAX5hMirZql0jJdEqxyx17qeso91GhT/YnrvUD5+oycLGNbK/52zvP6nxnquOFJoRzyJcALMRhsX3IlshEgcpWqXyTafQt+gE9OqQ7Y9fRlNIGzHjIzkzH8TJ6fhaYTxixjoUzsCsALghELAnRjKb23p2dfX9y/Gp9mp4YzsXC1p3gYguTmmRFwyoaXtEYeUCkKjgnoUAGXBxYhDhZTFuaNanTimUyof39SL1SHPT87TarD6zNvq3Vqb7fqB9WjQ9Ln9km05Itn2eyEhnhwOLysE2FbeSFtpwqielaKd6rlpYj36jruji1GaZ/MeJvzMjttPRC3TMbhdeG8nZS+3HMHUhg5cOsLNkyCSaX2JFFh5jFOA5CYZskpK/b4v1E2AxDs45r1nZPVEpRmE4Tl5sOtYB7/UBG/Yi1gYVCtI327+K7u4QQxQJh4caQ7sfpZ1pgXPLWKpSYdWtK7l5P3/XZfJrNxjGnF4AgEMUgigbAPR0p9moa2PZd01ri9SLwxKTKeVshTsbjTDwe29SSj8r8mWLhedgLYbs+QDYa27ETsTCR5FhR8Jg170nbc9pxTKq7866rW6JVmchk7EXJrabJXJTJ+UnOjwscFvQDvufGXQ5rQ6KqGczpBNwKJIMxdpxlKb/XreZtco7KpazVIlPPsdU0GfIgG4ucDuR2Au6y4UGfRUrgkT1kZxFtBZwAgsAoiuY8TMRlcTpIIUjEOUs0gnk9eNgPBIkoK8F7/wOx8tRDNBL9GgAAAABJRU5ErkJggg=="},"images":{"fallback":{"src":"/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/30f07/fish.jpg","srcSet":"/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/41624/fish.jpg 160w,\n/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/1b894/fish.jpg 320w,\n/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/30f07/fish.jpg 640w","sizes":"(min-width: 640px) 640px, 100vw"},"sources":[{"srcSet":"/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/6de5b/fish.avif 160w,\n/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/20389/fish.avif 320w,\n/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/8c32c/fish.avif 640w","type":"image/avif","sizes":"(min-width: 640px) 640px, 100vw"},{"srcSet":"/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/60b4d/fish.webp 160w,\n/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/5e011/fish.webp 320w,\n/PORTFOLIO_NEW_IMPROVED/static/66b45244f3af4eeea529e9a3aa16d609/90d07/fish.webp 640w","type":"image/webp","sizes":"(min-width: 640px) 640px, 100vw"}]},"width":700,"height":700}}},"tech":["Python","YOLOv8","PyTorch","OpenCV","Ultralytics"],"github":"https://github.com/Vinay0905/Fish-Detection-YOLOv8","external":"","cta":""},"html":"<p>A custom-trained YOLOv8 real-time object detection model for fish species identification and tracking in underwater imagery. Optimized to handle challenging conditions including low-light environments, high turbidity, and partial occlusion. The open-source project gained 50+ GitHub stars and has been referenced by other researchers working on marine biology computer vision tasks.</p>"}}]}}}