info Overview
PyTorch and TensorFlow/Keras are the primary deep learning frameworks used in DASCLAB research. PyTorch is preferred for research-stage model development and custom architectures, while TensorFlow/Keras is used in teaching (ML301 module) and deployment contexts. Both frameworks are applied to medical imaging, NLP, and crop yield prediction.
checklist Key Features
- Dynamic computation graphs (PyTorch): flexible model debugging
- Keras high-level API (TensorFlow): rapid prototyping
- torchvision and torchtext: domain-specific dataset tools
- TensorBoard: real-time training visualisation and profiling
- ONNX export: cross-framework model deployment
- Pre-trained model hub: ResNet, EfficientNet, BERT, XLM-R
photo_library Screenshots
Malaria parasite detection CNN output on blood smear
Model prediction overlay on test image
article Publications
Transfer Learning for Malaria Detection in Blood Smear Images