├── Deep learning loss functions.ipynb ├── INTRO ML 01 - Machine learning - a very basic introduction.ipynb ├── INTRO ML 02 - gradient descent for machine learning.ipynb ├── LICENSE.txt ├── README.md ├── SUPPLEMENTARY - Convolutions with sliding windows.ipynb ├── SUPPLEMENTARY - Gabor filters.ipynb ├── SUPPLEMENTARY - Standardisation.ipynb ├── TUTORIAL 01 - Using a pretrained conv-net - VGG net.ipynb ├── TUTORIAL 02 - Using a pretrained VGG-16 conv-net to find a peacock.ipynb ├── TUTORIAL 03 - Image region-level saliency using VGG-16 conv-net.ipynb ├── TUTORIAL 04 - Image pixel-level saliency using VGG-16 conv-net.ipynb ├── TUTORIAL 05 - Dogs vs cats with standard learning.ipynb ├── TUTORIAL 05 - Dogs vs cats with transfer learning and data augmentation.ipynb ├── TUTORIAL 05 - Dogs vs cats with transfer learning.ipynb ├── imagenet_classes.py ├── images ├── P1013781.JPG ├── P8131065.JPG └── fruit.jpg ├── requirements.txt └── utils.py /Deep learning loss functions.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/Deep learning loss functions.ipynb -------------------------------------------------------------------------------- /INTRO ML 01 - Machine learning - a very basic introduction.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/INTRO ML 01 - Machine learning - a very basic introduction.ipynb -------------------------------------------------------------------------------- /INTRO ML 02 - gradient descent for machine learning.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/INTRO ML 02 - gradient descent for machine learning.ipynb -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/LICENSE.txt -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/README.md -------------------------------------------------------------------------------- /SUPPLEMENTARY - Convolutions with sliding windows.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/SUPPLEMENTARY - Convolutions with sliding windows.ipynb -------------------------------------------------------------------------------- /SUPPLEMENTARY - Gabor filters.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/SUPPLEMENTARY - Gabor filters.ipynb -------------------------------------------------------------------------------- /SUPPLEMENTARY - Standardisation.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/SUPPLEMENTARY - Standardisation.ipynb -------------------------------------------------------------------------------- /TUTORIAL 01 - Using a pretrained conv-net - VGG net.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 01 - Using a pretrained conv-net - VGG net.ipynb -------------------------------------------------------------------------------- /TUTORIAL 02 - Using a pretrained VGG-16 conv-net to find a peacock.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 02 - Using a pretrained VGG-16 conv-net to find a peacock.ipynb -------------------------------------------------------------------------------- /TUTORIAL 03 - Image region-level saliency using VGG-16 conv-net.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 03 - Image region-level saliency using VGG-16 conv-net.ipynb -------------------------------------------------------------------------------- /TUTORIAL 04 - Image pixel-level saliency using VGG-16 conv-net.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 04 - Image pixel-level saliency using VGG-16 conv-net.ipynb -------------------------------------------------------------------------------- /TUTORIAL 05 - Dogs vs cats with standard learning.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 05 - Dogs vs cats with standard learning.ipynb -------------------------------------------------------------------------------- /TUTORIAL 05 - Dogs vs cats with transfer learning and data augmentation.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 05 - Dogs vs cats with transfer learning and data augmentation.ipynb -------------------------------------------------------------------------------- /TUTORIAL 05 - Dogs vs cats with transfer learning.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/TUTORIAL 05 - Dogs vs cats with transfer learning.ipynb -------------------------------------------------------------------------------- /imagenet_classes.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/imagenet_classes.py -------------------------------------------------------------------------------- /images/P1013781.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/images/P1013781.JPG -------------------------------------------------------------------------------- /images/P8131065.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/images/P8131065.JPG -------------------------------------------------------------------------------- /images/fruit.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/images/fruit.jpg -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/requirements.txt -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Britefury/deep-learning-tutorial-pydata/HEAD/utils.py --------------------------------------------------------------------------------