Follow these instructions to configure the Keras backend. You can also post bug reports and feature requests only in Github issues. Make sure to read our guidelines first. It is a reference to a literary image from ancient Greek and Latin literature, first found in the Odyssey , where dream spirits Oneiroi , singular Oneiros are divided between those who deceive men with false visions, who arrive to Earth through a gate of ivory, and those who announce a future that will come to pass, who arrive through a gate of horn.
Not all that men look for comes to pass. Two gates there are that give passage to fleeting Oneiroi; one is made of horn, one of ivory.
The Oneiroi that pass through sawn ivory are deceitful, bearing a message that will not be fulfilled; those that come out through polished horn have truth behind them, to be accomplished for men who see them.
Keras 2. Docs » Home Edit on GitHub. Use Keras if you need a deep learning library that: Allows for easy and fast prototyping through user friendliness, modularity, and extensibility. Supports both convolutional networks and recurrent networks, as well as combinations of the two. Read the documentation at Keras. Keras is compatible with: Python 2. Guiding principles User friendliness. Getting started: 30 seconds to Keras The core data structure of Keras is a model , a way to organize layers.
New issue. Jump to bottom. Labels stale. Copy link. I can't test this solution right now! I well try this evening. Can I print it with MKdocs? Still we don't have any PDF? Thanks a lot! Any chance one could be generated for the latest release? Keras Documentation. Docs » Home Edit on GitHub. Use Keras if you need a deep learning library that: Allows for easy and fast prototyping through total modularity, minimalism, and extensibility.
Supports both convolutional networks and recurrent networks, as well as combinations of the two. Supports arbitrary connectivity schemes including multi-input and multi-output training. Read the documentation at Keras. Keras is compatible with: Python 2. Guiding principles Modularity. Getting started: 30 seconds to Keras The core data structure of Keras is a model , a way to organize layers. Here's the Sequential model: from keras. For a more in-depth tutorial about Keras, you can check out: Getting started with the Sequential model Getting started with the functional API In the examples folder of the repository, you will find more advanced models: question-answering with memory networks, text generation with stacked LSTMs, etc.
When using the Theano backend: Theano See installation instructions. To install Keras, cd to the Keras folder and run the install command: sudo python setup. Support You can ask questions and join the development discussion: On the Keras Google group. On the Keras Gitter channel.
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