You will get an AI system to classify Uveal Melanoma using deep learning
Project details
I specialize in building deep learning and computer vision solutions for real-world problems. This project focuses on developing an accurate and efficient image classification system using PyTorch and advanced CNN/ResNet architectures. Unlike basic models, this solution includes proper data preprocessing, class balancing, model optimization, and interpretability using Grad-CAM. My approach ensures clean code, reliable performance, and practical AI results suitable for real applications.
Machine Learning Tools
ChatGPT, GitHub Copilot, Google Sheets, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorchWhat's included
| Service Tiers |
Starter
$15
|
Standard
$40
|
Advanced
$80
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 4 | 6 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
About Haris
AI Engineer | Computer Vision | PyTorch | YOLO
Sargodha, Pakistan - 4:05 pm local time
I develop intelligent AI systems for image classification, object detection, and medical imaging applications. My experience includes building deep learning models using CNNs, ResNet architectures, YOLO, OpenCV, and PyTorch.
Recently, I developed a deep learning-based eye disease classification system capable of detecting multiple ocular conditions from retinal images with high accuracy. The project included data preprocessing, augmentation, imbalance handling, Grad-CAM visualization, and model evaluation.
My Skills:
Python
Machine Learning
Deep Learning
Computer Vision
PyTorch
OpenCV
YOLO
CNN Models
Data Preprocessing
Medical Imaging AI
I focus on building accurate, efficient, and scalable AI solutions while maintaining clean code and reliable project delivery.
I am always eager to work on innovative AI and computer vision projects.
Steps for completing your project
After purchasing the project, send requirements so Haris can start the project.
Delivery time starts when Haris receives requirements from you.
Haris works on your project following the steps below.
Revisions may occur after the delivery date.
Evaluation & Results
Evaluate the model using accuracy, confusion matrix, and visualize results using graphs and Grad-CAM for better interpretation.