👋 Hello, I’m Nisar Ahmad Zamani
🧠 Machine Learning
I build machine learning solutions for classification, prediction, clustering, recommendation systems, and data analysis, with a focus on practical preprocessing, feature engineering, model evaluation, and deployment.
🔥 Deep Learning
I develop deep learning applications using PyTorch, neural networks, CNNs, Transformers, and fine-tuning, applying deep learning techniques to practical AI problems.
💬 Natural Language Processing
I work with NLP, text preprocessing, TF-IDF, tokenization, embeddings, text classification, and Transformer-based models to build intelligent systems for processing and understanding text.
🧩 Generative AI & LLMs
I build LLM-powered applications and RAG systems using embeddings, vector databases, semantic search, prompt engineering, document retrieval, and tool calling.
🤖 Agentic AI
I develop AI agents and multi-agent systems using LangChain and LangGraph, designing structured workflows, tool-calling systems, and agent orchestration for complex tasks.
🚀 Featured Projects
A selection of my projects demonstrating practical experience in Machine Learning, NLP, Generative AI, RAG, and Agentic AI.
CodePilotAI — Multi-Agent AI Software Engineering System
An AI-powered multi-agent system designed to support software engineering workflows through LLMs, LangChain, LangGraph, tool calling, task planning, code generation, and workflow orchestration.
TeleCare AI — RAG-Based Telecom Support Assistant
A domain-specific RAG customer support assistant that retrieves and synthesizes information from telecom documentation, FAQs, guides, and support tickets using LangChain, Hugging Face embeddings, ChromaDB, and LLMs.
ShopMind AI — Multi-Agent AI Shopping Assistant
A multi-agent AI shopping system that supports product search, filtering, review analysis, product image analysis, personalized recommendations, and shopping workflows using LangGraph, LangChain, Vision LLMs, and SQLite.
Medicine Recommendation System — Machine Learning & NLP
An intelligent recommendation system using Machine Learning and NLP techniques to generate relevant medicine recommendations from user-provided symptoms and medical information through text preprocessing, feature extraction, similarity-based recommendation, and data processing.
Market Segmentation — Machine Learning
A customer segmentation system using K-Means clustering, StandardScaler, the Elbow Method, PCA, and Decision Tree classification to identify customer groups and predict cluster assignments.
🛠️ Technical Expertise
Programming: Python, SQL
Machine Learning: Scikit-learn, Feature Engineering, Classification, Clustering, PCA, Model Evaluation
Deep Learning: PyTorch, Neural Networks, CNNs, Transformers, Fine-Tuning
NLP: NLP, Tokenization, TF-IDF, Text Classification, Embeddings, Hugging Face Transformers
Generative AI: LLMs, Prompt Engineering, RAG, Semantic Search, Embeddings
Agentic AI: LangChain, LangGraph, AI Agents, Multi-Agent Systems, Tool Calling
Databases & Vector Search: SQLite, FAISS, ChromaDB, Vector Databases
Deployment & Tools: FastAPI, Streamlit, Gradio, Docker, Git, GitHub, Hugging Face Spaces
💼 Experience
Machine Learning & Artificial Intelligence Intern
Redacto — VertexTech Labs Private Limited
Worked on Machine Learning, NLP, data preprocessing, exploratory data analysis, feature engineering, and AI-driven automation for data privacy and governance use cases.
🏆 Achievements
- 1st Place — Machine Learning Competition, RANA Durokhshan, 2025
- Top 1% Student — RANA Durokhshan Academy, 2026
- AI-Powered Chatbot Recognition — 2025
These achievements reflect my practical interest in Machine Learning, Artificial Intelligence, problem-solving, and AI application development.
📚 Certifications & Continuous Learning
I continuously strengthen my knowledge through professional training, technical learning, and hands-on AI/ML projects.
My learning and project experience cover:
Machine Learning · Deep Learning · NLP · Generative AI · LLMs · RAG · Agentic AI · PyTorch · LangChain · LangGraph
📄 Curriculum Vitae
For a detailed overview of my experience, technical skills, projects, and achievements:
📬 Let’s Connect
I’m open to Machine Learning and AI engineering opportunities, internships, research, collaboration, and practical AI projects.