{"action":"opened","issue":{"url":"https://api.github.com/repos/pkmital/tensorflow_tutorials/issues/17","repository_url":"https://api.github.com/repos/pkmital/tensorflow_tutorials","labels_url":"https://api.github.com/repos/pkmital/tensorflow_tutorials/issues/17/labels{/name}","comments_url":"https://api.github.com/repos/pkmital/tensorflow_tutorials/issues/17/comments","events_url":"https://api.github.com/repos/pkmital/tensorflow_tutorials/issues/17/events","html_url":"https://github.com/pkmital/tensorflow_tutorials/issues/17","id":159700609,"number":17,"title":"mplement Multi-Task deep learning with Tensorflow","user":{"login":"MammadTavakoli","id":12212802,"avatar_url":"https://avatars.githubusercontent.com/u/12212802?v=3","gravatar_id":"","url":"https://api.github.com/users/MammadTavakoli","html_url":"https://github.com/MammadTavakoli","followers_url":"https://api.github.com/users/MammadTavakoli/followers","following_url":"https://api.github.com/users/MammadTavakoli/following{/other_user}","gists_url":"https://api.github.com/users/MammadTavakoli/gists{/gist_id}","starred_url":"https://api.github.com/users/MammadTavakoli/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MammadTavakoli/subscriptions","organizations_url":"https://api.github.com/users/MammadTavakoli/orgs","repos_url":"https://api.github.com/users/MammadTavakoli/repos","events_url":"https://api.github.com/users/MammadTavakoli/events{/privacy}","received_events_url":"https://api.github.com/users/MammadTavakoli/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2016-06-10T19:01:05Z","updated_at":"2016-06-10T19:01:05Z","closed_at":null,"body":"How can implement Multi-Task deep learning with Tensorflow? how can i found any sample? \r\n\r\n!(https://camo.githubusercontent.com/9b5b091d632c5b923b706016ca15ee56e70c9958/687474703a2f2f322e62702e626c6f6773706f742e636f6d2f2d74736736742d63547857302f56626e31416c51776e72492f414141414141414143546b2f487a5548794e62547478492f73313630302f53637265656e25324253686f74253242323031352d30372d33302532426174253242253235453125323538342532353842253235453125323538352532354139253235453125323538342532353932253235453125323538352532354145253242362e35352e30312e706e67)"}}
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