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I will build custom image classification, clustering and deep learning models in python
About this Gig
Need a custom Machine Learning or Deep Learning model built in Python?
I build production-ready image classification and deep learning models using cutting-edge architectures CNNs, ResNet, EfficientNet, Vision Transformers (ViT), and transfer learning designed for both research accuracy and real-world deployment.
What I deliver:
- Image classification with modern architectures (ResNet, EfficientNet, ViT, Swin Transformer)
- Custom deep learning training on your dataset, including fine-tuning pretrained models
- Image segmentation using U-Net and DeepLabV3+
- Data preprocessing, augmentation, feature engineering, and EDA
- Full evaluation: accuracy, precision, recall, F1-score, confusion matrix, ROC-AUC
Why work with me:
- Strong grip on current SOTA architectures not just legacy CNNs
- Built for researchers needing reproducible, well-documented experiments
- Clean, optimized PyTorch/TensorFlow code with clear evaluation reports
- End-to-end support: dataset analysis training tuning final model
- Reliable, scalable solutions for research papers, startups, or business AI products
Message me before ordering share your dataset and use case, and I'll recommend the best architecture and approach for goal.
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Other Data Science & ML Services I Offer
FAQ
What type of image classification models can you build?
I build models using CNNs, ResNet, EfficientNet, and Vision Transformers (ViT) from simple binary classifiers to complex multi-class systems, depending on your accuracy and speed requirements.
Do I need to provide my own dataset?
Ideally yes, for best results on your specific use case. If you don't have one, I can help source, generate, or augment a suitable dataset, message me to discuss.
Can you train a deep learning model on my custom dataset?
Yes, this is my core service. I handle preprocessing, augmentation, training, and fine-tuning on pretrained architectures to match your data.
Which frameworks do you use for AI model development?
Primarily PyTorch and TensorFlow, along with scikit-learn for classical ML tasks and evaluation.
What evaluation metrics will you provide?
Accuracy, precision, recall, F1-score, confusion matrix, and ROC-AUC with a clear report explaining what the numbers mean for your use case.
Can you improve an existing machine learning or deep learning model?
Yes. I can review your current model, identify bottlenecks in architecture, data, or training strategy, and optimize it for better performance.
Will I receive the complete source code?
Yes, fully documented and structured so you or your team can maintain and extend it.
Can you build image segmentation models as well?
Yes, using U-Net, DeepLabV3+, and similar architectures for pixel-level classification tasks.
Can you reproduce a research paper or implement a specific AI model?
Yes, I can implement models from research papers and adapt them to your dataset and requirements.
Can you deploy the trained model as an API?
Yes, I can provide deployment support using FastAPI and Docker to integrate your trained machine learning model into applications or production systems.
