Arif Uz Zaman
AI & Data Analytics Specialist
Driving insights through intelligent data systems and cutting-edge machine learning solutions.
Tech Stack & Skills
Comprehensive expertise across the full data science and analytics ecosystem
Business Intelligence
● Process Mapping
● System Analysis
● Stakeholder Management
Analytics & Visualization
● Power BI
● Tableau
● Dash
● Data Visualization
● Interactive Dashboards
Machine Learning & AI
● Python
● GenAI
● Reinforcement Learning
● Deep Learning
● Computer Vision
Dashboard Development
● Process Mapping
● System Analysis
● Stakeholder Management
Programming & Databases
● Process Mapping
● System Analysis
● Stakeholder Management
Reporting Tools
● Process Mapping
● System Analysis
● Stakeholder Management
Featured Technologies
Python
Power BI
SQL
Machine Learning
TensorFlow
Fast API
Docker
AWS
Git
Tableau
Featured Projects
Showcase of machine learning, data analytics, and AI projects demonstrating practical problem-solving skills
A state-of-the-art Retrieval-Augmented Generation (RAG) system leveraging modern generative AI and vector search technologies. This project demonstrates how to build a production-grade system that enables advanced question answering, document search, and contextual generation on your own infrastructure—private, scalable, and fast.
Project Overview
This project showcases how to combine large language models (LLMs), local vector databases, and a modern Python web API for secure, high-performance knowledge and document retrieval. All LLM operations run locally—no data leaves your machine.
Ideal for applications in internal research, enterprise QA, knowledge management, or compliance-sensitive AI tasks.
Features
- Local LLM Inference: Runs entirely on your machine using Ollama and open-source models (e.g., Llama 3.1).
- Vector Database Search: Uses Qdrant for fast, scalable semantic retrieval.
- Flexible Document Ingestion: Upload PDF, DOCX, or TXT files for indexing and search.
- FastAPI Back End: High-concurrency, type-safe REST API with automatic documentation.
- Modern Python Package Management: Built with
uvfor blazing-fast dependency resolution. - Modular, Extensible Codebase: Clean architecture, easy to extend and maintain.
- Privacy and Security: No cloud calls—ideal for regulated sectors.
- Fully Containerizable: Easily deploy with Docker.
A lightning-fast local AI chat app using FastAPI, Python, and Ollama running Google Gemma3—streaming responses, ready for your portfolio, side projects, or prototypes!
Features
- Local LLM: Runs Google Gemma3 (
gemma3:1b,4b, etc.) on your own hardware using Ollama. - FastAPI backend: Optimized API with streaming responses for instant token display.
- Zero-JS frontend: Minimal HTML/JS for chat and live model replies—no frameworks needed.
- Easy deployment: Lockfile-based dependency management using uv.
- Docker-ready: Provided Dockerfile for reproducible builds, local development, or cloud/server hosting.
- Editable prompts: Full chat history, adjustable system prompt, model tag, and sampling controls.
- OpenAI-compatible option: Use with OpenAI client SDKs for future cloud portability.
A simple web application built with Streamlit that demonstrates how to serve a Machine Learning model in a user-friendly interface.
Features
- Upload input data (CSV or manual entry)
- Run predictions using a pre-trained ML model
- Display results in an interactive UI
- Basic data visualization (charts & tables)
- Easy to deploy locally or on cloud platforms
About Me
Passionate about turning data into intelligence and insights into impact
I’m a data enthusiast and AI practitioner passionate about solving real-world problems using data and automation. With hands-on experience in machine learning, data visualization, and business intelligence, I aim to deliver impactful insights and scalable AI solutions.
My journey in data science combines technical expertise with business acumen, enabling me to bridge the gap between complex algorithms and practical business outcomes. I specialize in end-to-end ML pipelines, from data exploration to model deployment.
When I’m not diving deep into datasets or training models, I enjoy exploring the latest developments in GenAI, contributing to open-source projects, and sharing knowledge with the data science community.
Ready to start your next project?
Let’s discuss how data science and AI can transform your business