Aspiring App Developer | AI Enthusiast | Computer Engineering Student | Tech Enthusiast
Hello! I'm Nevil Dhinoja, currently pursuing my Bachelor's degree in Computer Engineering at CHARUSAT University. With a strong foundation in programming and a growing interest in AI/ML and app development, I am passionate about building practical solutions and continuously learning new technologies.
- 🎓 Diploma: Completed in Computer Engineering at RK University.
- 🛠 Current Focus: Enhancing my AI/ML skills and problem-solving techniques.
- 🎯 Interests: App Development, AI/ML, Backend Development.
- Languages: Java, Python, PHP, C++
- App Development: Android Studio, Java, Flutter
- Databases: MySQL, SQLite, Firebase, MongoDB
- AI/ML: Machine Learning, Deep Learning, NLP, Flask, REST API
- Tools: Git, OpenAI, NOTEBOOKLM, VS Code, Postman, XAMPP
- Platforms: Android Studio, Django, Laravel, PyCharm
- Description: Fraud detection system using AI and ML models.
- Tech Stack: Python, Flask, MongoDB, scikit-learn
- Features: Real-time fraud detection, transaction monitoring, and anomaly detection.
- Achievement: Successfully implemented fraud detection with high accuracy.
- Description: A fully dynamic Java-based e-learning application.
- Tech Stack: Java, SQLite, Firebase
- Features: Course management, user-friendly UI, real-time tracking.
- Achievement: Successfully launched.
- Description: A collaborative coding platform for teams.
- Tech Stack: React.js, Node.js, Firebase
- Features: Real-time code collaboration, user authentication, project management.
- Achievement: Developed as part of a team project for university.
- Description: AI-powered tool for automatic code refactoring.
- Tech Stack: Python, OpenAI API, Flask
- Features: Improves code quality, suggests optimized code structures.
- Achievement: Successfully developed and shared on GitHub.
- Description: Development of NLP and deep learning models for automation and analytics.
- Tech Stack: Python, TensorFlow, spaCy, NLTK
- Features: Sentiment analysis, text classification, and language modeling.
- Achievement: Successfully trained models for various NLP tasks.
- Description: Google Colab-based project for detecting anomalies in videos using deep learning.
- Tech Stack: Python, TensorFlow, OpenCV
- Features: Real-time anomaly detection in surveillance videos.
- Achievement: Successfully implemented anomaly detection models.
| Project | Status | Milestones |
|---|---|---|
| Defraudo | Completed | Implemented AI-driven fraud detection. |
| The Learners | Completed | Successfully launched and available for use. |
| CodeCoLab | Completed | Developed as part of university project. |
| AI - CODE - REFACTOR | Completed | Successfully developed and posted on GitHub. |
| NLP & Deep Learning Models | Completed | Successfully trained and deployed models. |
| Video Anomaly Detection | Completed | Successfully implemented and tested deep learning models. |
- Email: [email protected]
- LinkedIn: LinkedIn Profile
- GitHub: GitHub Profile
Feel free to explore my repositories and reach out if you'd like to collaborate or discuss anything tech-related. I'm always excited to connect with like-minded individuals!