🚀 AI/ML Enthusiast | Deep Learning | Generative AI Developer
🔭 I’m working on AI-driven applications and scalable backend services
🌱 Learning cutting-edge AI/ML techniques and integrating them with web frameworks like Flask, Django, and FastAPI
I'm an AI/ML engineer with a passion for building intelligent systems using modern tools and frameworks. My focus areas are machine learning, deep learning, natural language processing, and generative AI models. I also enjoy integrating AI solutions with scalable backend technologies like Flask, FastAPI, and Django.
- 💡 I love experimenting with Generative AI models using Hugging Face and LangChain.
- 📚 Constantly learning new things in AI, Python, and cloud-native technologies.
- 🤝 Open to collaborating on exciting AI/ML projects and startups.
- Repo: Generative AI Models
- Description: Implemented and fine-tuned GPT-based text generation models and Stable Diffusion for image generation using Hugging Face. Integrated with LangChain for natural language understanding.
- Tech Stack: Python, Hugging Face, PyTorch, LangChain, Generative AI
- Repo: AI Chatbot FastAPI
- Description: Developed a scalable NLP-powered chatbot using Hugging Face Transformers and deployed via FastAPI for low-latency real-time conversations.
- Tech Stack: FastAPI, Python, Hugging Face, NLP
- Repo: ML Model Deployment Django
- Description: Deployed a machine learning model using Django for a web-based application. The project includes model training, serving via REST API, and integrating with a simple front end.
- Tech Stack: Django, Python, Scikit-Learn, Docker, REST API
- Repo: Image Classification Flask
- Description: Built a Flask-based microservice that performs image classification using a pre-trained deep learning model. The app is containerized using Docker.
- Tech Stack: Flask, TensorFlow, Keras, Docker, Python
- Programming Languages: Python, React Js, Next JS
- Frameworks: Flask, FastAPI, Django, Langchain
- AI/ML/DL: TensorFlow, PyTorch, Scikit-Learn, NLP, Hugging Face, LangChain, LlamaIndex
- Generative AI: GPT-3, DALL·E, Llama3.1, Gemma2:9b/27b, Retrieval augmented generation (RAG), Stable Diffusion, Transformers, Open Source/ Closed source Models
- Deployment: Docker, Kubernetes, AWS, Heroku
- Database: PostgreSQL, MongoDB, SQLite, Vector Database
- Tools: Git, GitHub, VS Code, Pycharm, DataSpell, Jupyter, Linux
- LangChain: Exploring multi-model NLP frameworks to enhance chatbot functionality and automate language tasks.
- Hugging Face Models: Fine-tuning pre-trained models for custom AI applications like summarization, sentiment analysis, and content generation.
- Generative AI: Delving into the world of Stable Diffusion, DALL·E, and GPT-based models for content creation and AI art.