Muhammad Rizwan

AI/ML Engineer | Python Developer | Creative Problem Solver

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👨‍💻 About Me

I'm a versatile Full Stack Python Developer and AI/ML Engineer with a passion for building intelligent systems and automation solutions. With expertise in Python development, machine learning, and automation technologies, I specialize in creating end-to-end solutions from robust backend systems to AI-powered applications. I excel in developing SaaS platforms, chatbots, and workflow automation using cutting-edge technologies.

🔧 Full Stack Python Developer crafting scalable web applications

🤖 AI Automation Expert specializing in workflow optimization

🧠 AI & ML Engineer building intelligent systems

💬 Chatbot Developer creating intelligent conversational agents

⚡ Workflow Automation Specialist with n8n expertise

🌐 SaaS Application Developer focused on scalable solutions

👁️ Expert in Computer Vision and image processing

📚 Lifelong learner exploring new technologies

🛠️ Skills & Technical Expertise

Backend Development

Python Django Flask FastAPI SQL PostgreSQL MongoDB RESTful APIs

AI & Machine Learning

TensorFlow PyTorch Scikit-learn Deep Learning Computer Vision NLP

Frontend Development

HTML5 CSS3 JavaScript React Streamlit Bootstrap

Data Science

Pandas NumPy Matplotlib Seaborn SQL Analytics

DevOps & Tools

Git Docker AWS Cloud Computing Linux/Unix

Computer Vision

OpenCV YOLO Image Processing Object Detection Image Segmentation

Testing & Quality

Unit Testing Debugging CI/CD Security Best Practices

Project Management

Agile/Scrum Team Collaboration Time Management Communication

AI Automation

n8n Workflow Automation Chatbots AI Agents Process Automation AutoML

SaaS Development

Multi-tenant Architecture OAuth & Security Database Scaling Cloud Deployment User Management Payment Integration

Projects

Medical Pills Detection

Advanced pill detection system using Ultralytics YOLO11, enabling accurate identification and classification of various medical pills with high precision.

YOLO11 Ultralytics Computer Vision
View on GitHub

Car Parts Detection & Segmentation

Implemented YOLOv11n-seg for precise car parts detection and segmentation using Ultralytics Hub, achieving high accuracy in automotive component identification.

YOLOv11 Segmentation Ultralytics
View on GitHub

Rice Leaf Disease Classification

Deep learning solution for detecting and classifying rice leaf diseases using YOLO, helping farmers identify plant health issues early for better crop management.

YOLO Classification Agriculture AI
View on GitHub

Airline Sentiment Analysis

Achieved 90% accuracy in airline review sentiment analysis using RNN, helping airlines improve customer service through data-driven insights.

RNN NLP Deep Learning
View on GitHub

Computer Vision Projects

A comprehensive collection of computer vision projects showcasing implementations of various algorithms and techniques in image processing and object detection.

OpenCV Deep Learning Image Processing
View on GitHub

AI Fruit & Vegetable Quality Checker

A deep learning system using Mask R-CNN, U-Net, and Detectron2 to classify and segment fruit and vegetable defects with detailed percentage-based results.

Mask R-CNN U-Net Detectron2
View on GitHub

HuggingFace HuggingFace Projects

Discover my contributions to the AI community through my HuggingFace profile. I actively share and maintain various AI models, datasets, and implementations focusing on Computer Vision and NLP tasks.

AI Models
Datasets
Spaces
Visit My HuggingFace Profile

Certifications

Kaggle Machine Learning Certification

Python for Everybody – Coursera

Computer Vision – Coursera

AI Certification – Ezitech Software House

Experience

Machine Learning Engineer Intern

Ezitech Software House 2023 - Present

Key Achievements:
  • Developed and deployed a high-performance medical pill detection system using YOLO11, achieving 95% accuracy in pill identification and classification
  • Implemented an automotive parts detection system using YOLOv11n-seg, improving component identification accuracy by 40%
  • Built and deployed scalable ML APIs using Flask and FastAPI, handling 1000+ requests per minute
  • Created interactive Streamlit dashboards for data visualization and model performance monitoring
  • Collaborated with cross-functional teams to integrate ML models into production environments
Technologies Used:
Python TensorFlow PyTorch YOLO OpenCV Flask FastAPI Streamlit Docker

AI/ML Freelance Developer

Self-Employed 2022 - Present

Key Projects:
  • Developed an agricultural disease detection system for crop monitoring using computer vision
  • Created custom chatbot solutions using advanced NLP techniques and transformer models
  • Implemented automated workflow systems using n8n and custom Python scripts
  • Built and deployed machine learning models for various business analytics applications
Technologies Used:
Python TensorFlow Hugging Face n8n Docker AWS

Education

BS Software Engineering

Islamia University Bahawalpur

Expected Graduation: 2025

Key Achievements:
  • CGPA: 3.8/4.0
  • President of the University AI/ML Society
  • Led multiple research projects in computer vision and deep learning
  • Published research paper on medical image analysis using deep learning
Relevant Coursework:
Machine Learning Deep Learning Computer Vision Natural Language Processing Data Structures Algorithms

Contact Me

rizwan@mlforge.dev

+923176277912