| # Multi-Label classification using Chest X-rays | |
| Using dataset from [Kaggle](https://www.kaggle.com/competitions/ranzcr-clip-catheter-line-classification/overview) | |
| First attempt at Pytorch | |
| At first, tried running on Kaggle GPU100 - very slow | |
| * Kaggle notebook [](https://colab.research.google.com/github/yxmauw/cxr-multilabel-clf/blob/main/enet-kaggle.ipynb) | |
| * Google colab notebook [](https://colab.research.google.com/github/yxmauw/cxr-multilabel-clf/blob/main/enet-colab.ipynb) | |
| ## References: | |
| 1. [Debugger cafe](https://debuggercafe.com/multi-label-image-classification-with-pytorch-and-deep-learning/) | |
| 1. [StackOverflow](https://stackoverflow.com/questions/71404067/using-more-than-1-metric-in-pytorch) | |
| 1. [Debugger cafe - model checkpoints](https://debuggercafe.com/saving-and-loading-the-best-model-in-pytorch/) | |