You will get a custom computer vision model for object detection/classification
Project details
I'm an AI/ML engineer specializing in computer vision, with hands-on experience building deep learning models for real-world detection and classification tasks — including fine-tuning models on satellite imagery for flood prediction as part of a full-scale AI system combining computer vision, IoT, and MLOps. I don't just train a model and hand it off — I deliver evaluated, documented, and (if needed) deployment-ready solutions, with automated retraining pipelines when your data changes over time. Whether you need to detect defects on a production line, classify objects in aerial imagery, or build a custom recognition system from scratch, I focus on models that are accurate, well-tested, and easy for your team to integrate. Clear communication throughout, realistic timelines, and code you actually understand — no black boxes.
Machine Learning Tools
OpenCV, Python, Tesseract OCRWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$700
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 20 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About Fakhira
AI/ML Engineer [ PyTorch , Computer Vision , NLP , Deep Learning ]
Karachi, Pakistan - 5:59 am local time
ML & Python Proficiency: I have strong command over Python and PyTorch, demonstrated through diverse projects including Diffusion Models for image denoising, Graph Neural Networks, and object detection pipelines.
Continuous Learning: I actively follow developments in LLM architectures and agent frameworks, and I am eager to apply this knowledge to solve real-world engineering challenges.
Steps for completing your project
After purchasing the project, send requirements so Fakhira can start the project.
Delivery time starts when Fakhira receives requirements from you.
Fakhira works on your project following the steps below.
Revisions may occur after the delivery date.
Preprocessing
Preprocess and prepare the dataset for training (cleaning, augmentation if needed).
Training
Train and fine-tune the computer vision model on your data.