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RitikOnWork/README.md

πŸ’« About Me:

I am Ritik Raj, an undergraduate student specializing in Artificial Intelligence and Machine Learning, driven by a strong interest in building data-driven and intelligent systems that solve real-world problems.

My primary focus lies in Machine Learning, Data Analysis, and Algorithmic Problem Solving. I actively work on transforming raw data into meaningful insights using Python and its ML ecosystem, while continuously strengthening my understanding of model building, evaluation, and optimization. Alongside ML, I maintain a solid foundation in Data Structures & Algorithms, which helps me write efficient, scalable, and production-ready code.

I believe in learning by building β€” applying concepts through hands-on projects in areas such as predictive modeling, data analytics, and intelligent automation. Currently, I am focused on deepening my ML fundamentals, experimenting with real datasets, and preparing for ML Engineer / SDE roles.

Always learning. Always building. πŸš€

🌐 Socials:

LinkedIn

πŸ’» Tech Stack:

C CSS3 HTML5 Java Python MySQL SQLite Pandas NumPy scikit-learn Matplotlib GitHub Git Arduino Raspberry Pi

πŸ“Š GitHub Stats:

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  1. iValidate iValidate Public

    iValidate is a smart and secure email validator that instantly checks email addresses for accuracy, helping businesses reduce bounces and improve deliverability with ease.

  2. CarPoolingApp CarPoolingApp Public

    RouteMesh is a modern, full-stack carpooling platform designed to connect drivers and passengers for smarter, greener travel. It features a stunning "Glassmorphism" UI, real-time ride searching, an…

    JavaScript

  3. AyurSutra AyurSutra Public

    AyurSutra is a Panchakarma patient management and therapy scheduling software that modernizes Ayurvedic healthcare delivery. It automates therapy scheduling, manages digital patient records, and se…

    JavaScript 2

  4. CropCast CropCast Public

    Trained an XGBoost regression model on 10 years of ICAR crop and weather data; achieved RMSE of 0.18 (tonnes/hectare) outperforming a baseline Linear Regression by 34%.

    Python