Azeem Aslam šŸ‘‹

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Azeem Aslam

About Me

I’m Azeem Aslam, a Computer Vision & Deep Learning Engineer with an MSc in IoT with Data Science. I specialize in training and deploying AI models (YOLOv8/v9, OpenAI Vision, CLIP) and building end-to-end applications with Streamlit, Flask, and Docker.

My expertise spans defect detection, object classification, and dataset automation, combining Python, PyTorch, and OpenCV skills with a focus on scalable, production-ready solutions. Whether in Agile teams or independent projects, I deliver innovative, future-ready AI systems that solve real-world challenges.

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What I Do

I offer professional services to bring your AI vision to life.

Custom Model Development

Training and fine-tuning state-of-the-art computer vision models (like YOLO) tailored to your specific data and use case.

AI Application Deployment

Deploying your models as scalable and robust applications using Docker, FastAPI, Streamlit, and cloud platforms.

Data Annotation & Preprocessing

Expert services in cleaning, augmenting, and annotating image and video data to ensure high-quality model training.

Skill Stack

A showcase of my technical capabilities.

Python (95%)

PyTorch/TF (90%)

YOLO (v8, v9) (92%)

OpenCV (88%)

Scikit-learn (85%)

Pandas (90%)

NumPy (94%)

Streamlit (85%)

Hugging Face (82%)

Docker (80%)

Git & GitHub (90%)

FastAPI (75%)

My Work

Project 1

Manufacturing Defects Detection

A Streamlit-based app to detect defects in 3D-printed components using YOLOv8.

Project 2

Real-time Vehicle Classification

A Hugging Face Spaces app that classifies two-wheeler vehicles from a webcam feed.

Project 3

Brain Tumor Detection (YOLOv9)

A deep learning model for medical imaging analysis, detecting brain tumors from MRI scans.

Project 4

AI-Powered Defect Detection

An advanced model for identifying subtle defects in industrial manufacturing lines.

Project 5

Weapon Detection YOLO8

A real-time weapon detection system for security and surveillance applications using YOLO.

Project 6

Industrial Object Detection and Segmentation

A robust approach for small-object detection in industrial settings using an improved YOLO model.

From My Blog Post

Azeem Aslam • 15 August, 2025

A Deep Dive into YOLOv9 for Real-Time Object Detection

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Azeem Aslam • 01 August, 2025

Deploying CV Models with Docker and FastAPI: A Beginner's Guide

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Azeem Aslam • 20 July, 2025

The Importance of Data Augmentation in Computer Vision

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