Browse categories
English
$
USD
Connect to your AI
I will develop a custom image classification model with deep learning in python
Machine Learning and Computer Vision Engineer
I’m a Computer Science graduate specializing in Machine Learning, Deep Learning, and Computer Vision. I help startups, businesses, and software teams build practical AI solutions for data, image, and ...
About this Gig
Struggling with inaccurate predictions, messy image datasets, or a deep learning project that isnt delivering results?
I will develop a custom image classification model tailored to your dataset and goals using deep learning in Python (TensorFlow or PyTorch).
What you get:
- Custom image classification model (binary or multi-class)
- Deep learning pipeline with TensorFlow or PyTorch
- Image preprocessing, augmentation, and dataset preparation
- Model training, validation, testing, and hyperparameter tuning
- Full performance evaluation: accuracy, precision, recall, F1-score
- Confusion matrix and clear result visualizations
- Clean, organized source code + project documentation
Perfect for:
- Academic or research projects
- Multi-category image classification
- Computer vision prototypes
- Business or product image categorization
Every solution is built around your data and requirements. You will understand exactly how the model performs with measurable metricsnot just predictions. Results depend on dataset quality, size, and complexity.
Ready to turn your image data into a working, accurate AI solution?
Message me today with a short description of your dataset and goals, and lets get started.
My Portfolio
Other Data Science & ML Services I Offer
FAQ
What type of image classification projects do you handle?
I build custom binary and multi-class image classification models for academic, research, and business projects. Whether you need product categorization, medical image classification, landscape recognition, or any other custom categories, I create a tailored deep learning solution based on your data
Can you train the model on my custom dataset?
Yes. Simply provide your labeled image dataset, and I will handle data preparation, model training, evaluation, and delivery of the agreed results. Message me with sample images first so I can confirm suitability and recommend the best package.
How many image classes can you handle?
I support both binary and multi-class classification. The exact number depends on your dataset size, quality, and the package you choose. Share your class list and a few sample images, and I will confirm the scope before you order.
Which technologies and frameworks do you use?
I primarily work with Python, TensorFlow/Keras, PyTorch, OpenCV, and supporting libraries (NumPy, Pandas, etc.). I select the best tools and architecture (CNN or transfer learning) according to your dataset and project requirements.
Do you use CNN and transfer learning?
Yes. I use custom CNN architectures and modern transfer learning models (ResNet, EfficientNet, MobileNet, Vision Transformers, etc.) when they deliver better accuracy and faster training for your specific task.
Will I receive the source code?
Yes. Clean, well-organized, and commented source code (Jupyter Notebook or Python scripts) is included in all packages. Higher packages include more structured and production-ready code.
Will you provide an inference / prediction script?
Yes. An easy-to-use inference script is included in the Standard and Premium packages (or can be added as an extra to the Basic package) so you can run predictions on new images after delivery.
What evaluation results will I receive?
You will receive clear performance metrics including accuracy, precision, recall, F1-score, classification report, confusion matrix, and sample predictions with visualizations — so you can fully understand how the model performs.
Can you guarantee a specific accuracy?
No. Model performance depends on dataset quality, class balance, image diversity, labeling accuracy, and task complexity. I always evaluate and optimize the model based on your data, but I cannot promise a fixed accuracy percentage before reviewing the dataset. I will give you an honest assessment
What should I send before ordering?
Please message me with: 1- A sample of your dataset (or a few example images from each class) 2- The list of classes 3- A short description of your goal
