Lasagne: Difference between revisions
From charlesreid1
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==Lasagne== | |||
Github repo: https://github.com/Lasagne/Lasagne | Github repo: https://github.com/Lasagne/Lasagne | ||
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Documentation: https://lasagne.readthedocs.io/en/latest/ | Documentation: https://lasagne.readthedocs.io/en/latest/ | ||
Lasagne recipes (examples, models, notebooks, etc.): https://github.com/Lasagne/ | Using Lasagne via Docker: https://lasagne.readthedocs.io/en/latest/user/installation.html#docker | ||
* Can use CPU Docker image, or GPU Docker image (via nvidia-docker) | |||
==Github== | |||
===Lasagne=== | |||
* https://github.com/Lasagne/Lasagne - main repo | |||
* https://github.com/Kaixhin/dockerfiles - Docker images for Lasagne/Theano | |||
* https://agentnet.readthedocs.io/en/latest/index.html - AgentNet is a toolkit for deep reinforcement learning agent design | |||
===Resources/Teaching=== | |||
* https://github.com/Lasagne/Recipes - Lasagne recipes (examples, models, notebooks, etc.) | |||
* https://github.com/Vict0rSch/deep_learning - Deep learning tutorials and resources for Lasagne+Keras | |||
* https://github.com/lesley2958/deep-learning-python - introduction to deep learning with theano/lasagne | |||
* https://github.com/yandexdataschool/Practical_DL - practical deep learning course resources | |||
==Implementations of Papers/Example Networks== | |||
* https://github.com/mikesj-public/convolutional_autoencoder - convolutional autoencoder in lasagne/jupyter notebook | |||
* https://github.com/ferrine/gelato - Bayesian network layers for Lasagne | |||
* https://github.com/joelmoniz/gogh-figure - van Gogh style transfer | |||
* https://github.com/zalandoresearch/spatial_gan - spatial generative adversarial neural network (one network generates, one network tries to spot the fake stuff) | |||
* https://github.com/luizgh/lasagne_basics - training Lasagne CNN on MNIST data set | |||
* https://github.com/FredericGodin/DynamicCNN - dynamic CNN in Lasagne | |||
* https://github.com/TimSalimans/weight_norm - illustration of weight normalization in Lasagne | |||
=Flags= | =Flags= | ||
Revision as of 22:41, 14 October 2017
What is it
Lasagne is a high-level interface for Theano.
Links
Lasagne
Github repo: https://github.com/Lasagne/Lasagne
Documentation: https://lasagne.readthedocs.io/en/latest/
Using Lasagne via Docker: https://lasagne.readthedocs.io/en/latest/user/installation.html#docker
- Can use CPU Docker image, or GPU Docker image (via nvidia-docker)
Github
Lasagne
- https://github.com/Lasagne/Lasagne - main repo
- https://github.com/Kaixhin/dockerfiles - Docker images for Lasagne/Theano
- https://agentnet.readthedocs.io/en/latest/index.html - AgentNet is a toolkit for deep reinforcement learning agent design
Resources/Teaching
- https://github.com/Lasagne/Recipes - Lasagne recipes (examples, models, notebooks, etc.)
- https://github.com/Vict0rSch/deep_learning - Deep learning tutorials and resources for Lasagne+Keras
- https://github.com/lesley2958/deep-learning-python - introduction to deep learning with theano/lasagne
- https://github.com/yandexdataschool/Practical_DL - practical deep learning course resources
Implementations of Papers/Example Networks
- https://github.com/mikesj-public/convolutional_autoencoder - convolutional autoencoder in lasagne/jupyter notebook
- https://github.com/ferrine/gelato - Bayesian network layers for Lasagne
- https://github.com/joelmoniz/gogh-figure - van Gogh style transfer
- https://github.com/zalandoresearch/spatial_gan - spatial generative adversarial neural network (one network generates, one network tries to spot the fake stuff)
- https://github.com/luizgh/lasagne_basics - training Lasagne CNN on MNIST data set
- https://github.com/FredericGodin/DynamicCNN - dynamic CNN in Lasagne
- https://github.com/TimSalimans/weight_norm - illustration of weight normalization in Lasagne