Name: Sanjay S Nayak
Location: Bangalore, India
Education: B.E. in Information Science & Engineering @ BMSIT&M (Graduating 2027)
Focus Areas: Full-Stack Development (MERN) | Machine Learning | Deep Learning | Natural Language Processing | Intelligent Web Applications
Fun Fact: I build things from scratch to understand how they actually work- 🔭 Building intelligent applications using Machine Learning, Deep Learning, and modern AI technologies.
- 🌐 Developing scalable MERN Stack applications with real-time communication using WebRTC and Socket.io.
- 📚 Continuously learning by building projects from scratch and understanding the underlying algorithms.
Languages
AI / ML / Deep Learning
Frontend
Backend & APIs
Databases
DevOps & Tools
Design & Productivity
| Project | Domain | Tech Stack | Highlights |
|---|---|---|---|
| CreditWise — Loan Approval Prediction | Supervised Learning | Scikit-Learn, Pandas | 87.5% accuracy with 79% precision for loan approval prediction |
| SmartCart — Customer Segmentation | Unsupervised Learning | Scikit-Learn, K-Means, PCA | Identified 4 customer personas for targeted marketing |
| PowerPulse — Energy Output Prediction | Deep Learning (Regression) | PyTorch, Scikit-Learn | Feedforward neural network achieving R² = 93.55% and RMSE = 4.29 MW |
| DatePal — Date Fruit Classification | Deep Learning (Classification) | PyTorch, Scikit-Learn | Classified 7 date fruit varieties with 94.44% accuracy |
| VisionNet — CNN Image Classification | Computer Vision | PyTorch, Torchvision | CNN trained on CIFAR-10 achieving 73.89% test accuracy |
| SentimentRNN — IMDB Movie Review Sentiment Analysis | Natural Language Processing | PyTorch, NLTK, Scikit-Learn | End-to-end RNN achieving 86.96% accuracy on 50,000 IMDB movie reviews |
- 🤖 Large Language Models (LLMs)
- 🤖 Large Language Models (LLMs)
- 📚 Retrieval-Augmented Generation (RAG)
- 🧠 Reinforcement Learning
- 🤖 Agentic AI Systems
- 🎨 Generative AI & Diffusion Models
- 🎭 Generative Adversarial Networks (GANs)