{"id":125744,"date":"2018-11-07T08:43:02","date_gmt":"2018-11-07T00:43:02","guid":{"rendered":"https:\/\/lrxjmw.cn\/?p=125744"},"modified":"2018-10-30T10:45:39","modified_gmt":"2018-10-30T02:45:39","slug":"deep-learning-model","status":"publish","type":"post","link":"https:\/\/lrxjmw.cn\/deep-learning-model.html","title":{"rendered":"\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b"},"content":{"rendered":"
mnist\uff1a\u5bf9\u6765\u81eaMNIST\u6570\u636e\u96c6\u7684\u6570\u5b57\u8fdb\u884c\u5206\u7c7b\u7684\u57fa\u672c\u6a21\u578b\u3002\u6700\u5f00\u59cb\u8bbe\u8ba1\u51fa\u6765\u7684\u76ee\u7684\u662f\u7528\u4e8e\u8bc6\u522b\u6570\u5b57\uff0c\u540c\u65f6\u4e5f\u662f\u6df1\u5ea6\u5b66\u4e60\u7684\u4e00\u4e2a\u6837\u4f8b\u3002<\/p>\n
resnet\uff1a\u4e00\u4e2a\u6df1\u5ea6\u6b8b\u5dee\u7f51\u7edc\uff0c\u53ef\u7528\u4e8eCIFAR-10\u548cImageNet\u76841000\u4e2a\u7c7b\u522b\u7684\u6570\u636e\u96c6\u8fdb\u884c\u5206\u7c7b\u3002\u7531\u4e8e\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u7ec3\u4e60\u6b21\u6570\u8fbe\u5230\u67d0\u4e00\u4e2a\u503c\u65f6\u8bc6\u522b\u51c6\u786e\u7387\u4ee5\u53ca\u8bc6\u522b\u6027\u80fd\u4f1a\u4e0b\u964d\uff0c\u56e0\u800c\u5f00\u53d1\u51fa\u4e86\u53ef\u4ee5\u63d0\u9ad8\u5b66\u4e60\u6df1\u5ea6\u7684\u7f51\u7edc\u3002<\/p>\n
wide_deep\uff1a\u5c06\u5e7f\u6cdb\u7684\u6a21\u578b\u548c\u6df1\u5ea6\u7f51\u7edc\u76f8\u7ed3\u5408\u7684\u6a21\u578b\uff0c\u7528\u4e8e\u5bf9\u4eba\u53e3\u666e\u67e5\u6536\u5165\u6570\u636e\u8fdb\u884c\u5206\u7c7b\u3002\u7ecf\u8fc7\u5b66\u4e60\u540e\uff0c\u795e\u7ecf\u7f51\u7edc\u53ef\u4ee5\u901a\u8fc7\u5176\u4e2d\u51e0\u4e2a\u6570\u636e\u7684\u503c\u63a8\u65ad\u51fa\u5176\u4ed6\u6570\u636e\u7684\u503c\u3002<\/p>\n
adversarial_crypto\uff1a\u4fdd\u62a4\u4e0e\u5bf9\u6297\u5f0f\u795e\u7ecf\u5bc6\u7801\u5b66\u7684\u901a\u4fe1\u3002<\/p>\n
adversarial_text\uff1a\u5177\u6709\u5bf9\u6297\u8bad\u7ec3\u7684\u534a\u76d1\u7763\u5e8f\u5217\u5b66\u4e60\u3002<\/p>\n
attention_ocr\uff1a\u56fe\u50cf\u8bc6\u522b\u6587\u672c\u63d0\u53d6\u6a21\u578b\uff08\u7528\u4e8e\u9ad8\u5e72\u6270\u7684\u73b0\u5b9e\u573a\u666f\uff09\u3002<\/p>\n
autoencoder\uff1a\u5404\u79cd\u81ea\u52a8\u7f16\u7801\u5668\u3002<\/p>\n
brain_coder\uff1a\u5e26\u5f3a\u5316\u5b66\u4e60\u7684\u7a0b\u5e8f\u7efc\u5408\u5668\u3002<\/p>\n
cognitive_mapping_and_planning\uff1a\u4e3a\u89c6\u89c9\u5bfc\u822a\u5b9e\u73b0\u57fa\u4e8e\u7a7a\u95f4\u8bb0\u5fc6\u7684\u6620\u5c04\u548c\u89c4\u5212\u4f53\u7cfb\u7ed3\u6784\u3002<\/p>\n
compression\uff1a\u4f7f\u7528\u9884\u5148\u8bad\u7ec3\u7684\u5269\u4f59GRU\u7f51\u7edc\u538b\u7f29\u548c\u89e3\u538b\u7f29\u56fe\u50cf\u3002<\/p>\n
deeplab\uff1a\u7528\u4e8e\u8bed\u4e49\u56fe\u50cf\u5206\u5272\u7684\u6df1\u5ea6\u6807\u7b7e\u3002<\/p>\n
delf\uff1a\u7528\u4e8e\u5339\u914d\u548c\u68c0\u7d22\u56fe\u50cf\u7684\u6df1\u5c42\u5c40\u90e8\u7279\u5f81\u3002<\/p>\n
differential_privacy\uff1a\u6765\u81ea\u591a\u4f4d\u6559\u5e08\u7684\u5b66\u751f\u9690\u79c1\u4fdd\u62a4\u6a21\u578b\u3002<\/p>\n
domain_adaptation\uff1a\u57df\u5206\u79bb\u7f51\u7edc\u3002<\/p>\n
gan\uff1a\u751f\u6210\u5bf9\u6297\u5f0f\u7f51\u7edc\u3002<\/p>\n
im2txt\uff1a\u7528\u4e8e\u8f6c\u6362\u56fe\u50cf\u5b57\u5e55\u4e3a\u6587\u672c\u7684\u795e\u7ecf\u7f51\u7edc\u3002<\/p>\n
inception\uff1a\u7528\u4e8e\u8ba1\u7b97\u673a\u89c6\u89c9\u7684\u6df1\u5ea6\u5377\u79ef\u7f51\u7edc\u3002<\/p>\n
learning_to_remember_rare_events\uff1a\u7528\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u5927\u578b\u7ec8\u8eab\u8bb0\u5fc6\u6a21\u5757\u3002<\/p>\n
lfads\uff1a\u7528\u4e8e\u5206\u6790\u795e\u7ecf\u79d1\u5b66\u6570\u636e\u7684\u987a\u5e8f\u53d8\u5206\u81ea\u52a8\u7f16\u7801\u5668\u3002<\/p>\n
lm_1b\uff1a\u4ee5\u5341\u4ebf\u5355\u8bcd\u4e3a\u57fa\u51c6\u6d4b\u8bd5\u7684\u8bed\u8a00\u5efa\u6a21\u3002<\/p>\n
maskgan\uff1a\u7528GAN\u751f\u6210\u6587\u672c\u3002<\/p>\n
namignizer\uff1a\u8bc6\u522b\u5e76\u751f\u6210\u540d\u79f0\u3002<\/p>\n
neural_gpu\uff1a\u9ad8\u5ea6\u5e76\u884c\u7684\u795e\u7ecf\u8ba1\u7b97\u673a\u3002<\/p>\n
neural_programmer\uff1a\u7528\u903b\u8f91\u548c\u6570\u5b66\u8fd0\u7b97\u589e\u5f3a\u7684\u795e\u7ecf\u7f51\u7edc\u3002<\/p>\n
next_frame_prediction\uff1a\u901a\u8fc7\u4ea4\u53c9\u5377\u79ef\u7f51\u7edc\u8fdb\u884c\u6982\u7387\u6027\u7684\u4e0b\u4e00\u5e27\u5408\u6210\u3002<\/p>\n
object_detection\uff1a\u5b9a\u4f4d\u548c\u8bc6\u522b\u5355\u4e2a\u56fe\u50cf\u4e2d\u7684\u591a\u4e2a\u5bf9\u8c61\u3002<\/p>\n
pcl_rl\uff1a\u7528\u4e8e\u51e0\u79cd\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5\u7684\u4ee3\u7801\uff0c\u5305\u62ec\u8def\u5f84\u4e00\u81f4\u6027\u5b66\u4e60\u3002<\/p>\n
ptn\uff1a\u7528\u4e8e\u4e09\u7ef4\u7269\u4f53\u91cd\u5efa\u7684\u900f\u89c6\u53d8\u6362\u7f51\u3002<\/p>\n
qa_kg\uff1a\u6a21\u5757\u7f51\u7edc\uff0c\u7528\u4e8e\u5728\u77e5\u8bc6\u56fe\u4e0a\u8fdb\u884c\u95ee\u9898\u89e3\u7b54\u3002<\/p>\n
real_nvp\uff1a\u4f7f\u7528\u5b9e\u503c\u975e\u5bb9\u91cf\u4fdd\u7559\uff08\u771f\u5b9eNVP\uff09\u53d8\u6362\u7684\u5bc6\u5ea6\u4f30\u8ba1\u3002<\/p>\n
rebar\uff1a\u79bb\u6563\u6f5c\u53d8\u91cf\u6a21\u578b\u7684\u4f4e\u65b9\u5dee\uff0c\u65e0\u504f\u5dee\u68af\u5ea6\u4f30\u8ba1\u3002<\/p>\n
resnet\uff1a\u6df1\u5c42\u548c\u5e7f\u6cdb\u7684\u6b8b\u4f59\u7f51\u7edc\u3002<\/p>\n
skip_thoughts\uff1a\u9012\u5f52\u795e\u7ecf\u7f51\u7edc\u53e5 \u2013 \u77e2\u91cf\u7f16\u7801\u5668\u3002<\/p>\n
slim\uff1aTF-Slim\u4e2d\u7684\u56fe\u50cf\u5206\u7c7b\u6a21\u578b\u3002<\/p>\n
street\uff1a\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u4ece\u56fe\u50cf\u4e2d\u8bc6\u522b\u8857\u9053\u7684\u540d\u79f0\uff08\u4ec5\u9650\u4e8e\u6cd5\u56fd\uff09\u3002<\/p>\n
swivel\uff1a\u7528\u4e8e\u751f\u6210\u590d\u5408\u8bcd\u7684Swivel\u7b97\u6cd5\u3002<\/p>\n
syntaxnet\uff1a\u81ea\u7136\u8bed\u8a00\u8bed\u6cd5\u7684\u795e\u7ecf\u6a21\u578b\u3002<\/p>\n
tcn\uff1a\u4ece\u591a\u89c6\u70b9\u89c6\u9891\u5b66\u4e60\u7684\u81ea\u6211\u76d1\u7763\u8868\u793a\u3002<\/p>\n
textsum\uff1a\u5e8f\u5217\u5230\u5e8f\u5217\u4e0e\u6587\u672c\u6458\u8981\u7684\u5173\u6ce8\u6a21\u578b\u3002<\/p>\n
transformer\uff1a\u7a7a\u95f4\u8f6c\u8bd1\u7f51\u7edc\uff0c\u53ef\u4ee5\u5bf9\u7f51\u7edc\u5185\u7684\u6570\u636e\u8fdb\u884c\u7a7a\u95f4\u5904\u7406\u3002<\/p>\n
video_prediction\uff1a\u7528\u795e\u7ecf\u5e73\u6d41\u9884\u6d4b\u672a\u6765\u7684\u89c6\u9891\u5e27\uff08\u7c7b\u4f3c\u4e8enext_frame_prediction\uff09\u3002<\/p>\n
\u5173\u4e8e\u5176\u4e2d\u7684\u51e0\u4e2a\u9879\u76ee\uff1a<\/p>\n
Mnist\u5b9e\u9645\u4e0a\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u89c6\u89c9\u8ba1\u7b97\u6570\u636e\u96c6\uff0c\u76ee\u7684\u5927\u6982\u5c31\u662f\u4e3a\u7528\u673a\u5668\u5b66\u4e60\u7ec3\u4e60\u5bf9\u6570\u636e\u8fdb\u884c\u5904\u7406\u3002\u5b83\u672c\u8eab\u53ef\u80fd\u6ca1\u6709\u975e\u5e38\u6709\u7528\u7684\u4e00\u4e2a\u5e94\u7528\uff0c\u53ea\u662f\u5b66\u4e60\u673a\u5668\u5b66\u4e60\u7684\u2018\u966a\u7ec3\u2019\u3002Mnist\u4e3b\u8981\u7528\u6765\u8bad\u7ec3\u56fe\u50cf\u8bc6\u522b\u76f8\u5173\u7684\u673a\u5668\u5b66\u4e60\u6a21\u5757<\/p>\n
https:\/\/github.com\/zalandoresearch\/fashion-mnist<\/a><\/p>\n \u8fd9\u91cc\u6709\u4e00\u4e2a\u5f88\u6709\u540d\u4e5f\u5f88\u6709\u8da3\u7684mnist\u6570\u636e\u96c6fashion-mnist\uff0c\u753160,000\u4e2a\u793a\u4f8b\u7684\u8bad\u7ec3\u96c6\u548c10,000\u4e2a\u793a\u4f8b\u7684\u6d4b\u8bd5\u96c6\u7ec4\u6210\u3002\u6bcf\u4e2a\u793a\u4f8b\u90fd\u662f28\u00d728\u7070\u5ea6\u56fe\u50cf\uff0c\u4e0e10\u4e2a\u7c7b\u522b\u7684\u6807\u7b7e\u76f8\u5173\u8054\u3002\uff08T\u6064\/\u4e0a\u8863\uff0c\u88e4\u5b50\uff0c\u5957\u5934\u886b\uff0c\u8fde\u8863\u88d9\uff0c\u5927\u8863\uff0c\u51c9\u978b\uff0c\u886c\u886b\uff0c\u8fd0\u52a8\u978b\uff0c\u5305\uff0c\u811a\u8e1d\u9774\uff09\uff0c\u4f5c\u8005\u5236\u4f5c\u8fd9\u4e2a\u6570\u636e\u96c6\u7684\u672c\u610f\u662f\u7528\u4f5c\u9a8c\u8bc1mnist\u7b97\u6cd5\u7684\u57fa\u51c6\u3002<\/p>\n wide_deep\u7ed9\u7684\u5219\u662f\u7528\u4eba\u53e3\u666e\u67e5\u6536\u5165\u6570\u636e\u9884\u6d4b\u6536\u5165\uff0c\u6b63\u5982\u5176\u540d\u5b57\u6240\u8bf4\u7684\uff0c\u8fd9\u662f\u4e00\u4e2a\u6df1\u5bbd\u6a21\u578b\u3002\u4e5f\u57fa\u672c\u662f\u7528\u6765\u9a8c\u8bc1tensorflow\u5bf9\u6df1\u5bbd\u6a21\u578b\u5904\u7406\u7684\u5e94\u7528\u3002<\/p>\n \u6b64\u5916\uff0c\u4ecb\u7ecd\u4e24\u4e2a\u96be\u5ea6\u8f83\u4f4e\u7684tensorflow\u7684\u9879\u76ee\uff1a<\/p>\n \u9a8c\u8bc1\u7801\u8bc6\u522b\uff1a<\/p>\n