You will get Reproduce and implement any ML research paper
Project details
I will reproduce and implement any Machine Learning or Deep Learning research paper, translating complex mathematical formulas into clean, structured Python code.
Whether you need to replicate a state-of-the-art model from arXiv, or fine-tune a model from Hugging Face/GitHub for your own datasets, I deliver verified results.
What I can help you implement:
✓ Model Architecture: Coding custom CNNs, Transformers, GNNs, or GANs.
✓ Training Pipelines: Writing training, validation, and testing scripts.
✓ Benchmark Verification: Comparing model results with the paper's original scores.
✓ Code Translation: Converting legacy research code (e.g., MATLAB/C++) into clean PyTorch/TensorFlow.
What you will receive:
• Modular, well-documented Python source code
• Model weights file (trained on your dataset or public baseline)
• Detailed technical summary report (PDF/Markdown) detailing findings
Let's bring cutting-edge AI research to life!
Whether you need to replicate a state-of-the-art model from arXiv, or fine-tune a model from Hugging Face/GitHub for your own datasets, I deliver verified results.
What I can help you implement:
✓ Model Architecture: Coding custom CNNs, Transformers, GNNs, or GANs.
✓ Training Pipelines: Writing training, validation, and testing scripts.
✓ Benchmark Verification: Comparing model results with the paper's original scores.
✓ Code Translation: Converting legacy research code (e.g., MATLAB/C++) into clean PyTorch/TensorFlow.
What you will receive:
• Modular, well-documented Python source code
• Model weights file (trained on your dataset or public baseline)
• Detailed technical summary report (PDF/Markdown) detailing findings
Let's bring cutting-edge AI research to life!
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceWhat's included
| Service Tiers |
Starter
$180
|
Standard
$300
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 7 days | 10 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | ||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | |||
Ontology | |||
Source Code | - | - | |
Taxonomy | - | - |
Frequently asked questions
About Hafiz
Computer Vision & Machine Learning Expert | YOLO, OCR & Deep Learning
Gujranwala, Pakistan - 2:20 am local time
or visual monitoring is a cost your business should not be carrying.
I eliminate it, with production-ready Computer Vision and Machine
Learning systems built around your exact workflow, not generic templates.
✅ IBM-Certified AI, Machine Learning, and Computer Vision Engineer
✅ YOLO object detection, OCR data extraction, image segmentation, tracking, and deployment
✅ Clean Python code, progress demos, documentation, and deployment-ready delivery
Need to automate detection, inspection, OCR, or video analysis with AI?
I help businesses build reliable Computer Vision systems for real-time
object detection, document data extraction, image segmentation, defect
detection, visual quality inspection, image classification, video
analytics, and machine learning prediction tasks.
My focus is not only model accuracy. I also build the complete workflow
around it: data preparation, model training, evaluation, optimization,
API integration, deployment, and documentation.
Services I Can Help With:
▸ Object Detection and Tracking
YOLO-based detection and tracking for CCTV, drones, traffic monitoring,
safety compliance, retail analytics, vehicle detection, people counting,
and automation.
▸ OCR and Document AI
Data extraction from invoices, forms, PDFs, IDs, receipts, scanned
documents, tables, and business paperwork.
▸ Image Segmentation
Custom segmentation models for medical imaging, satellite imagery, remote
sensing, industrial inspection, defect detection, and object masks.
▸ Visual Quality Control
Automated inspection systems for factories, production lines, PPE safety,
product defects, anomaly detection, and quality monitoring.
▸ Video Analytics
Object counting, motion detection, behavior analysis, real-time video
processing, camera-based monitoring, and surveillance automation.
▸ Machine Learning
Classification, regression, forecasting, churn prediction, anomaly
detection, and business prediction models.
Tech Stack:
Computer Vision: OpenCV, YOLOv8, YOLOv11, YOLOv26, RT-DETR, Mask R-CNN, U-Net, SAM
OCR: Tesseract, EasyOCR, PaddleOCR
Tracking: DeepSORT, ByteTrack
Machine Learning: Scikit-learn, XGBoost, LightGBM, CatBoost
Deep Learning: PyTorch, TensorFlow, CNNs, Transfer Learning, Fine-Tuning
Deployment: FastAPI, Flask, Streamlit, Docker, REST APIs
Data: Pandas, NumPy, Feature Engineering, Model Evaluation, Data Annotation
Project Highlights:
▸ Fire and Smoke Detection
Trained a YOLO model on 22,000+ images for real-time drone surveillance.
▸ Vehicle Speed Monitoring
Built a YOLO + DeepSORT pipeline for speed estimation and violation detection.
▸ PPE Safety Compliance
Created a computer vision system for helmet and safety vest detection from CCTV feeds.
▸ Brain Tumor Segmentation
Built a medical image segmentation model for detecting and masking tumor
regions from MRI scans.
▸ Factory Quality Control
Built an image classification and inspection system for detecting product
defects on a moving conveyor belt.
▸ Invoice Data Extraction
Developed an OCR pipeline to convert scanned invoices into structured Excel output.
▸ Business Prediction
Built machine learning pipelines for churn prediction, forecasting, and anomaly detection.
How I Work:
▸ Free consultation to understand your exact requirement
▸ Clear project plan with milestones before any code is written
▸ Weekly progress updates with demo videos or screenshots
▸ Clean, documented, deployment-ready code delivery
▸ Post-delivery support for questions and minor fixes
If you need a Computer Vision, OCR, Object Detection, Image Segmentation,
Video Analytics, Image Processing, or Machine Learning system, send me
your dataset, sample images, video, PDF, or project description.
I will reply with a clear technical plan, timeline, and honest estimate.
Steps for completing your project
After purchasing the project, send requirements so Hafiz can start the project.
Delivery time starts when Hafiz receives requirements from you.
Hafiz works on your project following the steps below.
Revisions may occur after the delivery date.
Paper Review & Feasibility Analysis
I will review the paper's math, architectures, and dataset details to verify feasibility and map out the coding process.
Model Architecture Implementation
I will code the neural network layers, custom activation functions, or architectures from scratch in PyTorch or TensorFlow.