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Achievement: Pull Sharkx2Achievement: QuickdrawAchievement: YOLO

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SACHIN-S-2004/README.md

 About me✌🏻 sachin-s-2004

Coding

  • 💡 I’m an MCA Student at Saintgits College of Engineering, Kerala, India

  • 🔐 I’m currently into AI | Machine Learning | Deep Learning

  • 💻 Interested in Web Development and Applied AI, designing and deploying intelligent systems using Machine Learning and Deep Learning

  • 🛡️ Planning to dive into Cybersecurity after mastering the ML & DL stack

  • 🚀 Passionate about bridging AI and real-world problem solving

  • 🌱 Always learning — currently exploring model deployment and MLOps practices


GitHub followers


💻 Tech Stack

🗣️ Languages
c    cplusplus    java    python    r

🎨 Frontend
html5    css3    javascript    react    nextjs    tailwindcss    bootstrap    vite

⚙️ Backend
nodejs    express    php    flask    dotnet

🗄️ Database
mysql    mongodb

🤖 AI / ML
tensorflow    keras    scikitlearn    opencv    pandas    numpy    matplotlib

🚀 Deployment & Tools
aws    docker    jenkins    apache    vercel    git    npm


🚧 Projects

  • CrackIt 📝

    CrackIt is an aptitude testing platform that enables users to assess their knowledge across diverse categories and improve through targeted feedback. Designed for learners and job-seekers alike, it offers structured tests, performance tracking, and a pathway to continuous growth.

    React Node.js Express.js MongoDB JWT

  • Framzy 🎞️

    Framzy is a wallpaper exploration hub that lets users explore, search, and download high-quality images across diverse categories. Designed for personalization and aesthetics, it offers curated collections, responsive browsing, and a seamless experience with dark/light mode and animated backgrounds.

    React Node.js Express.js MongoDB TailwindCSS

  • BeneFit 💪🏻

    BeneFit is an AI-powered personalized diet and fitness recommendation system that combines machine learning with medical rule-based logic to deliver safe, goal-oriented nutrition plans. Built using PHP, Flask, and MySQL.

    PHP Flask MySQL scikit-learn Python

  • Sentiment-Analysis 😊

    A Flask web app powered by TensorFlow and Keras that uses an Artificial Neural Network to classify text reviews as Positive, Negative, or Neutral. It applies text tokenization and sequence padding to process input, delivering real-time sentiment predictions with a clean, responsive UI.

    Flask TensorFlow Keras Python ANN

  • Image-Compression 🖼️

    A modern Flask web application built with Flask, OpenCV, and Scikit-Learn. It applies K-Means clustering to reduce color complexity, significantly shrinking file size while preserving visual quality, with live preview and compression statistics.

    Flask OpenCV scikit-learn Python K-Means


📊 GitHub Stats




🌐 Socials

LinkedIn email

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  1. CrackIt CrackIt Public

    CrackIt is an aptitude testing platform that enables users to assess their knowledge across diverse categories and improve through targeted feedback. Designed for learners and job-seekers alike, it…

    JavaScript

  2. Framzy Framzy Public

    Framzy is a wallpaper exploration hub that lets users explore, search, and download high-quality images across diverse categories. Designed for personalization and aesthetics, it offers curated col…

    JavaScript

  3. BeneFit BeneFit Public

    BeneFit is an AI-powered personalized diet and fitness recommendation system that combines machine learning with medical rule-based logic to deliver safe, goal-oriented nutrition plans. Built using…

    PHP

  4. QGen QGen Public

    QGen is a web-based application designed to assist educators in creating, organizing, and managing question repositories, as well as generating question papers for educational institutions.

    PHP

  5. Image-Compression Image-Compression Public

    A modern Flask web application built with Flask, OpenCV, and Scikit-Learn. It applies K-Means clustering to reduce color complexity, significantly shrinking file size while preserving visual qualit…

    Jupyter Notebook

  6. Handwritten-Digit-Recognition-using-MNIST Handwritten-Digit-Recognition-using-MNIST Public

    A Flask web app that uses a CNN model trained on MNIST to recognize handwritten digits (0–9) with high accuracy, offering canvas drawing and image upload with real-time predictions.

    Jupyter Notebook