Just a few keras-things I found useful.
- https://github.com/joeddav/devol
- https://github.com/maxpumperla/hyperas
- https://github.com/keras-team/keras-contrib
- Accelerating Deep Learning with Multiprocess Image Augmentation in Keras (accompanying blog post)
- ml-tools: Tools for common machine learning tasks using Tensorflow and Keras
- https://github.com/kuza55/keras-extras
- keras-multi-gpu: Multi-GPU data-parallel training in Keras
- keras_callbacks_example: Keras Callback Examples
- https://github.com/raghakot/keras-resnet
- https://github.com/XifengGuo/CapsNet-Keras
- https://github.com/kentsommer/keras-inceptionV4
- https://github.com/fchollet/deep-learning-models
- https://github.com/titu1994/DenseNet
- BatchRenormalization: Batch Renormalization algorithm implementation in Keras
- mlp: Multilayer Perceptron Keras wrapper for sklearn
- Image-Classification-Mobile: Sandbox for training large-scale image classification networks for embedded systems, including collection of pretrained classification models for Keras with MXNet backend
- https://github.com/merantix/picasso
- https://github.com/raghakot/keras-vis
- https://github.com/fchollet/hualos
- quiver: Interactive convnet features visualization for Keras (homepage)
- hera: Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser
- picard: Easily declare large spaces of (keras) neural networks and run (hyperopt) optimization experiments on them (homepage)
- keras-visualize-activations: Activation Maps Visualization for Keras
- https://github.com/sachinruk/deepschool.io
- https://github.com/leriomaggio/deep-learning-keras-tensorflow
- https://github.com/kailashahirwar/cheatsheets-ai
- https://github.com/donnemartin/data-science-ipython-notebooks
- https://github.com/xingkongliang/Keras-Tutorials
- https://github.com/anujgupta82/DeepNets/tree/master/Keras/Keras_from_scratch
- https://github.com/chibuk/simple-cnn-keras-colaboratory