Md Al Amin

This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.

This repository features deep learning models implemented with TensorFlow and PyTorch, including FNN, CNN, RNN, LSTM, GAN, Transfer Learning, and Transformer & BERT, GPT Each model is built from scratch with explanations, optimized training, and comparisons between frameworks, offering hands-on experience in understanding core deep learning concept

Generative-AI-with-Langchain-and-Huggingface explores cutting-edge generative AI concepts. Topics include LangChain basics, ChromaDB, conversational memory, vector databases, document Q&A with RAG, text summarization (refine chains, YT/video summarization), building LLMs, search engines, and advanced tools/agents.

An end-to-end AI pipeline that scrapes LinkedIn profile and post data to predict 16-personality (MBTI) types using a RAG-enhanced LLM fine-tuned with LoRA. It automates data collection, preprocessing, storage in PostgreSQL, and personality inference from real-world behavioral and linguistic patterns.

A practical FastAPI-based repository for building and deploying APIs, starting from web and database projects to serving ML, DL, and LLM models. Ideal for learning scalable AI deployment and modern API design with Python, Pydantic, and production-ready tools like LangChain and HuggingFace.

A comprehensive implementation of the HuggingFace and Langchain-academy Agentic AI course. Explore LLM-powered agents using transformers-agents, custom tools, multi-step reasoning, and real-world deployment workflows across Hugging Face's agent framework and inference APIs.