{"action":"created","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/1399","labels_url":"https://api.github.com/repos/fchollet/keras/issues/1399/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/1399/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/1399/events","html_url":"https://github.com/fchollet/keras/issues/1399","id":124676097,"number":1399,"title":"Development goals: January-February 2016","user":{"login":"fchollet","id":710255,"avatar_url":"https://avatars.githubusercontent.com/u/710255?v=3","gravatar_id":"","url":"https://api.github.com/users/fchollet","html_url":"https://github.com/fchollet","followers_url":"https://api.github.com/users/fchollet/followers","following_url":"https://api.github.com/users/fchollet/following{/other_user}","gists_url":"https://api.github.com/users/fchollet/gists{/gist_id}","starred_url":"https://api.github.com/users/fchollet/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fchollet/subscriptions","organizations_url":"https://api.github.com/users/fchollet/orgs","repos_url":"https://api.github.com/users/fchollet/repos","events_url":"https://api.github.com/users/fchollet/events{/privacy}","received_events_url":"https://api.github.com/users/fchollet/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":18,"created_at":"2016-01-03T22:47:18Z","updated_at":"2016-01-18T02:14:29Z","closed_at":null,"body":"Last month, [we delivered on our key development goals for the period](https://github.com/fchollet/keras/issues/1174). Keras has made great strides in code quality and documentation.\r\n\r\nHere's an update with our new goals. On one side, we will continue improving the codebase and feature set of Keras. On the other side, we will start focusing more on providing the community with a wealth of real applications, rather than just library features. As deep learning engineering becomes increasingly commoditized (most notably by Keras), Keras needs to move up the ladder of abstraction and start providing value at the application level in order to stay relevant for the next 5 years.\r\n\r\nThese applications will roughly fall into two categories:\r\n\r\n- end-to-end demonstrations of how to tackle simple ML problems with Keras (e.g. text classification from raw text files, image classification from raw images), packaged as standalone reusable applications\r\n- state-of-the-art examples targeted to researchers and advanced users, mostly in the generative / artistic domain.\r\n\r\n## Development:\r\n\r\n- fix ongoing issues with RNN masking (#1310)\r\n- introduce abstract layers `TimeDistributed`, `Highway`, `Residual` (residual learning).\r\n- better support for inception-style architectures, and improvements to the Graph API\r\n\r\n## Applications:\r\n\r\n- a Keras model catalog, where each model would include Python code, a JSON configuration, and saved pre-trained weights in HDF5.\r\n- a Keras blog introducing interesting Keras applications, hopefully on a weekly or biweekly basis\r\n- a DeepDream implementation\r\n- a NeuralStyle implementation\r\n- Caffe support (#921)\r\n- interactive dialogue and question answering systems(s)\r\n- music generation implementation(s)\r\n\r\nAs a closing note, I am noticing that the October-December period, rich in ML conferences, has seen the release of over 15 research papers using Keras for their experiments (plus an unknowable count of papers that used Keras without citing it --a majority of papers never cite the open source frameworks they use). This is a positive sign : )"},"comment":{"url":"https://api.github.com/repos/fchollet/keras/issues/comments/172408430","html_url":"https://github.com/fchollet/keras/issues/1399#issuecomment-172408430","issue_url":"https://api.github.com/repos/fchollet/keras/issues/1399","id":172408430,"user":{"login":"fchollet","id":710255,"avatar_url":"https://avatars.githubusercontent.com/u/710255?v=3","gravatar_id":"","url":"https://api.github.com/users/fchollet","html_url":"https://github.com/fchollet","followers_url":"https://api.github.com/users/fchollet/followers","following_url":"https://api.github.com/users/fchollet/following{/other_user}","gists_url":"https://api.github.com/users/fchollet/gists{/gist_id}","starred_url":"https://api.github.com/users/fchollet/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fchollet/subscriptions","organizations_url":"https://api.github.com/users/fchollet/orgs","repos_url":"https://api.github.com/users/fchollet/repos","events_url":"https://api.github.com/users/fchollet/events{/privacy}","received_events_url":"https://api.github.com/users/fchollet/received_events","type":"User","site_admin":false},"created_at":"2016-01-18T02:14:29Z","updated_at":"2016-01-18T02:14:29Z","body":"@lukedeo hosting would be inexpensive. It's bandwidth that is the problem. Keras has around 30k active users, so we could realistically expect several TBs of downloads every month, which would potentially cost hundreds every month."}}