Hi, I'm Shubham Patel!

🎓 I have a background in Computer Science, and my journey began with game development, creating interactive worlds. Today, my primary passion is Artificial Intelligence and Machine Learning, where I focus on building impactful solutions.

• 🤖 Artificial Intelligence & Machine Learning
  Developing intelligent systems that solve real-world problems. My work spans deep learning, natural language processing (NLP), computer vision, and reinforcement learning. I enjoy taking projects from model development to deployment on cloud platforms.

• 🌐 Cloud & Full-Stack Deployment
  Experienced in deploying ML applications on AWS (ECS Fargate), integrating FastAPI, Gradio, and building scalable pipelines for real-time inference.

• 🧠 AI Research and Exploration
  Exploring generative AI, interpretable ML, and large language models (LLMs), with a focus on continuous learning and cutting-edge innovation.

• 🕹️ Game Development Enthusiast
  I continue to explore Unity and Unreal Engine, blending creativity with technical problem-solving.

• 🛠️ Software Development
  Building efficient applications using Python, PyTorch, TensorFlow, and leveraging cloud platforms like AWS and GCP.

I'm motivated by the idea that AI can transform industries and creativity, not just by automating tasks but by enabling entirely new solutions and experiences.

Here are some of my recent projects demonstrating real-world AI/ML applications:

• Telco Customer Churn Prediction – End-to-end ML platform with XGBoost, Optuna, and MLflow; deployed on AWS ECS Fargate with a Gradio UI. Live Demo | GitHub
• Semantic Book Recommender – Hugging Face deployment using LangChain, OpenAI embeddings, and FAISS for semantic search. Live Demo | GitHub
• RAG Resume Assistant – Retrieval-Augmented Generation system for querying resumes using LangChain, FAISS, and OpenAI. Live Demo | GitHub
• Trash Detection (Capstone) – Real-time trash detection for robots using YOLOv11n, deployed in embedded environments with Python and OpenCV.
• Traffic Congestion Prediction – Big data pipeline using PySpark on GCP, processing 94.5M+ rows of NYC traffic data with real-time dashboards.
• Leafio – Plant Disease Detection – Android app powered by CNN model served via Flask API for real-time crop disease detection.

Feel free to reach out here on GitHub or on LinkedIn.
I'm always excited to discuss AI projects, research ideas, cloud deployments, or creative applications of technology!

🚀 Let's innovate, build, and shape the future together!