Hello! I’m Shubham Raj, a passionate Software Developer, with a strong focus on Full-Stack Development, Data Science, Machine Learning, Artificial Intelligence. I enjoy solving complex problems and sharing my knowledge with the developer community.
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Languages & Frameworks:
- Python, Java, JavaScript (Node.js, React, Express)
- C++, PHP, TypeScript
- Django, Flask, Laravel
- SQL, NoSQL (MongoDB, PostgreSQL)
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Machine Learning & AI:
- Deep Learning, Reinforcement Learning (RL), Computer Vision
- Natural Language Processing (NLP)
- TensorFlow, Keras, PyTorch, Scikit-learn
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Cloud & DevOps:
- AWS, Azure, Google Cloud
- Docker, Kubernetes, CI/CD Pipelines
- Terraform, Ansible
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Web Development:
- MERN Stack (MongoDB, Express.js, React, Node.js)
- HTML5, CSS3, JavaScript, Bootstrap, Tailwind CSS
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Software Engineering:
- Object-Oriented Programming (OOP), Design Patterns
- Algorithms & Data Structures
- Agile & Test-Driven Development (TDD)
- Exploring advancements in Quantum Computing
- Mastering Serverless Architectures with AWS Lambda
- Enhancing expertise in Deep Reinforcement Learning for AI Game Bots
- Improving container orchestration skills with Kubernetes & Helm
- Email: meshubham111213@gmail.com, shubu17225@gmail.com
- LinkedIn: https://www.linkedin.com/in/shubham-raj-428538201/
- Website/Portfolio: yourwebsite.com
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[ OWNIFY — E-commerce website]
Tech Stack: [Html, CSS, TypeScript, Java, Spring Boot, MySQl, Node.js]
Description: [OWNIFY is an e-commerce website with a responsive user interface, which contains features including user registration, product catalog, shopping cart, checkout process, and admin panel. This project employs a robust tech stack, including HTML, CSS, TypeScript, Java, Spring Boot, Hibernate, MySQL, Node.js and Angular.]. -
[ Early Detection Of Breast Cancer Using Machine Learning Techniques]
Tech Stack: [Python, Machine Learning]
Description: [Developed early detection of breast cancer using machine learning techniques, achieving 96% accuracy on the test set. Optimized Random Forest Algorithm, achieving 96.5% accuracy and enhanced generalization.]. -
[ Bus Ticket Booking System]
Tech Stack: [HTML, PHP]
Description: [Developed a web application using PHP and HTML to allow users to search for and book bus tickets online. The project involved implementing features such as user registration and login, bus search and filtering, seat selection and booking, payment processing.].
- 🏆 Completed the [Robotic Process Automation(RPA) Virtual Internship] on [AICTE]
- 🏅 Developed a [Machine Learning-AI Virtual Internship] model achieving [ 92% Accuracy]
- 🎓 Graduated with [B.Tech] in [Computer Science and Engineering]
- [OWNIFY — E-commerce website]: [OOWNIFY is a dynamic e-commerce platform with a responsive and user-friendly interface. It features user registration, a product catalog, a shopping cart, a streamlined checkout process, and an admin panel for efficient management. The project leverages a robust tech stack, including HTML, CSS, JavaScript, React.js, TypeScript, Java, Spring Boot, Hibernate, MySQL, Node.js, and Angular. These technologies ensure seamless functionality, scalability, and an engaging user experience. This project highlights my expertise in full-stack development and my ability to create efficient, feature-rich web applications tailored for modern e-commerce needs.]
- [Early Detection Of Breast Cancer Using Machine Learning Techniques]: [In this project, I developed a machine learning-based system for the early detection of breast cancer. The system leverages three algorithms Logistic Regression, Decision Tree, and Random Forest to analyze medical data and predict cancerous outcomes. After thorough evaluation, the Random Forest model achieved a high accuracy of 96%, showcasing its effectiveness in making reliable predictions. This project demonstrates my ability to apply machine learning techniques to solve critical real world healthcare challenges, emphasizing accuracy and reliability in medical diagnostics.]
- [Bus Ticket Booking System]: [The Bus Ticket Booking System is a web application designed to simplify the process of searching and booking bus tickets online. Built using HTML, CSS, and PHP, the platform provides a seamless user experience with essential features such as user registration and login, bus search and filtering, seat selection and booking, and secure payment processing. This project showcases my proficiency in web development by creating a functional and user-friendly application. It emphasizes my ability to integrate front-end and back-end technologies to deliver a responsive and efficient solution for modern travel needs.]
If you're interested in collaborating or want to talk about any of my projects, feel free to reach out!
Thank you for visiting my GitHub profile! 😊