{"id":47031,"date":"2018-03-29T03:38:08","date_gmt":"2018-03-28T18:38:08","guid":{"rendered":"https:\/\/www.sejuku.net\/blog\/?p=47031"},"modified":"2024-05-06T11:46:23","modified_gmt":"2024-05-06T02:46:23","slug":"47031","status":"publish","type":"post","link":"https:\/\/www.sejuku.net\/blog\/47031","title":{"rendered":"\u3010TensorFlow\u3011\u516c\u5f0f\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306b\u306f\u306a\u3044AutoEncoder\u3092\u96c6\u3081\u3066\u307f\u305f"},"content":{"rendered":"

AutoEncoder\uff08\u30aa\u30fc\u30c8\u30a8\u30f3\u30b3\u30fc\u30c0\uff1a\u81ea\u5df1\u7b26\u53f7\u5316\u5668\uff09<\/strong><\/span>\u3092\u3054\u5b58\u77e5\u3067\u3057\u3087\u3046\u304b\uff1f<\/p>\n

AutoEncoder\u306f\u3001\u3068\u3066\u3082\u6709\u540d\u306a\u30e2\u30c7\u30eb\u3067\u3059<\/strong><\/span>\u304c\u3001TensorFlow\u306e\u516c\u5f0f\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306b\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/p>\n

\u305d\u306e\u305f\u3081\u3001TensorFlow\u3092\u4f7f\u3044\u59cb\u3081\u305f\u65b9\u306f\u3001AutoEncoder\u3092\u3054\u5b58\u77e5\u306a\u3044\u65b9\u3082\u591a\u3044\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n

\u4eca\u56de\u306f\u3001<\/p>\n

\u30fbAutoEncoder\u306f\u4f55\u304c\u30b9\u30b4\u3044\u306e\u304b
\n\u30fbAutoEncoder\u3092\u5b9f\u969b\u306b\u52d5\u304b\u3057\u3066\u307f\u3088\u3046<\/strong><\/span><\/p>\n

\u3092\u984c\u6750\u306b\u3001\u624b\u3092\u52d5\u304b\u3057\u306a\u304c\u3089AutoEncoder\u306e\u7406\u89e3\u3092\u6df1\u3081\u308b\u5207\u3063\u639b\u3051\u4f5c\u308a\u3092\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n

AutoEncoder\u3068\u306f<\/h2>\n

AutoEncoder<\/strong><\/span>\u306f\u3001\u4ee5\u4e0b\u306e\u753b\u50cf\u306e\u3088\u3046\u306b\u5165\u529b\u753b\u50cf\uff081\u884c\u76ee\u306e\u753b\u50cf\uff09<\/strong><\/span>\u304b\u3089\u5fa9\u5143\u753b\u50cf\uff082\u884c\u76ee\u306e\u753b\u50cf\uff09<\/strong><\/span>\u3092\u751f\u6210\u3059\u308b\u305f\u3081\u306e\u91cd\u307f\u884c\u5217\u3092\u5b66\u7fd2\u3059\u308b\u30e2\u30c7\u30eb\u3067\u3059\u3002<\/p>\n

\"tens-ae01\"<\/p>\n

\u8a00\u3044\u304b\u3048\u308b\u3068\u3001\u5165\u529b\u753b\u50cf\u3092\u5727\u7e2e\u3057\u3066\u3082\uff08\uff1d\u5165\u529b\u5c64\u3088\u308a\u3082\u5c0f\u3055\u306a\u6b21\u5143\u306e\u5c64\u3092\u901a\u3063\u3066\u3082\uff09\u3001\u5165\u529b\u753b\u50cf\u3068\u540c\u4e00\u306e\u5fa9\u5143\u753b\u50cf\u3092\u751f\u6210\u3067\u304d\u308b\u3088\u3046\u306a\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6c42\u3081\u308b<\/strong><\/span>\u306e\u304cAutoEncoder\u3067\u3059\u3002<\/p>\n

\u5143\u3005\u306f\u3001\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6c7a\u5b9a\u3059\u308b\u305f\u3081\u306b\u7814\u7a76\u304c\u9032\u3081\u3089\u308c\u305fAutoEncoder\u3067\u3057\u305f\u304c\u3001\u3053\u306e\u76ee\u7684\u3067\u306f\u4f7f\u308f\u308c\u306a\u304f\u306a\u308a\u3001\u4eca\u3067\u306f\u753b\u50cf\u306e\u30ce\u30a4\u30ba\u9664\u53bb<\/strong><\/span>\uff08\u30ce\u30a4\u30ba\u3042\u308a\u306e\u5165\u529b\u753b\u50cf\u3092AutoEncoder\u306b\u901a\u3057\u3066\u3001\u30ce\u30a4\u30ba\u7121\u3057\u306e\u5fa9\u5143\u753b\u50cf\u3092\u751f\u6210\u3059\u308b\uff09\u7a0b\u5ea6\u3067\u3057\u304b\u4f7f\u308f\u308c\u306a\u304f\u306a\u3063\u305f\u3088\u3046\u3067\u3059\u3002<\/p>\n

AutoEncoder\u306e\u4f5c\u3063\u3066\u307f\u305f\u8a18\u4e8b\u307e\u3068\u30813\u9078<\/h2>\n

\u6709\u7528\u6027\u306b\u3064\u3044\u3066\u306f\u3001\u5c06\u6765\u306b\u671f\u5f85\u3059\u308b\u3068\u3057\u3066\u3001\u3053\u3053\u304b\u3089\u306f\u3001\u7c21\u5358\u306aAutoEncoder\u3092\u4f5c\u3063\u3066\u516c\u958b\u3057\u3066\u3044\u308b\u4eba\u305f\u3061\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u52d5\u304b\u3057\u3066\u307f\u307e\u3059\u3002<\/strong><\/span><\/p>\n

\u306a\u304a\u3001\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u4ee5\u4e0b\u306e\u8a18\u4e8b\u3067\u7d39\u4ecb\u3057\u305f\u65b9\u6cd5\u3067\u3001GPU\u7248TensorFlow<\/strong><\/span>\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u305f\u74b0\u5883\u3067\u3001AutoEncoder\u3092\u52d5\u4f5c\u3055\u305b\u307e\u3059\u3002<\/p>\n \n

\n
\n
\n \n <\/div>\n
\n
TensorFlow\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u65b9\u6cd5\u307e\u3068\u3081\uff01\u3067\u304d\u306a\u3044\u6642\u306e\u5bfe\u51e6\u6cd5\u3082\u7d39\u4ecb<\/div>\n
\u66f4\u65b0\u65e5\uff1a2025\u5e7412\u670826\u65e5<\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/a>\n \n

TensorFlow\u3067\u6a5f\u68b0\u5b66\u7fd2\u3068\u622f\u308c\u308b: AutoEncoder\u3092\u4f5c\u3063\u3066\u307f\u308b – Qiita<\/h3>\n

\"tens-ae02\"<\/p>\n

\u53c2\u8003\uff1ahttps:\/\/qiita.com\/mokemokechicken\/items\/8216aaad36709b6f0b5c<\/a><\/p>\n

MNIST\u30c7\u30fc\u30bf<\/strong><\/span>\u3092\u5727\u7e2e\u3001\u5fa9\u5143\u3059\u308bAutoEncoder\u3092\u4f5c\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n

\u30d7\u30ed\u30b0\u30e9\u30e0\u306e\u4fdd\u5b58\u3068\u4fee\u6b63<\/h4>\n

\u8a18\u4e8b\u306b\u66f8\u304b\u308c\u3066\u3044\u308b\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u300cAutoEncoder.py\u300d<\/strong><\/span>\u3068\u3057\u3066\u4fdd\u5b58\u3057\u307e\u3059\u3002<\/p>\n

TensorFlow\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u30a2\u30c3\u30d7\u306b\u3068\u3082\u306a\u3044\u3001\u4e00\u90e8\u306e\u66f8\u304d\u304b\u305f\u3092\u5909\u66f4\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n

\uff081\uff09\u4fee\u6b63\u524d\uff1a<\/p>\n

# For tensorboard learning monitoring\r\ntf.scalar_summary("l2_loss", loss)<\/pre>\n
\u4fee\u6b63\u5f8c\uff1a<\/p>\n
# For tensorboard learning monitoring\r\ntf.summary.scalar("l2_loss", loss)<\/pre>\n
\uff082\uff09\u4fee\u6b63\u524d\uff1a<\/p>\n
# Prepare Session\r\ninit = tf.initialize_all_variables()\r\nsess = tf.Session()\r\nsess.run(init)\r\nsummary_writer = tf.train.SummaryWriter('summary\/l2_loss', graph_def=sess.graph_def)<\/pre>\n
\u4fee\u6b63\u5f8c\uff1a<\/p>\n
# Prepare Session\r\ninit = tf.global_variables_initializer()\r\nsess = tf.Session()\r\nsess.run(init)\r\nsummary_writer = tf.summary.FileWriter('summary\/l2_loss', graph=sess.graph)<\/pre>\n
\uff083\uff09\u4fee\u6b63\u524d\uff1a<\/p>\n
# Collect Summary\r\nsummary_op = tf.merge_all_summaries()<\/pre>\n
\u4fee\u6b63\u5f8c\uff1a<\/p>\n
# Collect Summary\r\nsummary_op = tf.summary.merge_all()<\/pre>\n
\uff084\uff09\u4fee\u6b63\u524d\uff1a<\/p>\n
# Draw Input Data(x)\r\nplt.subplot(2*N_ROW, N_COL, 2*row*N_COL+col+1)\r\nplt.title('IN:%02d' % i)\r\nplt.imshow(data.reshape((28, 28)), cmap="magma", clim=(0, 1.0), origin='upper')\r\nplt.tick_params(labelbottom="off")\r\nplt.tick_params(labelleft="off")\r\n\r\n# Draw Output Data(y)\r\nplt.subplot(2*N_ROW, N_COL, 2*row*N_COL + N_COL+col+1)\r\nplt.title('OUT:%02d' % i)\r\ny_value = y.eval(session=sess, feed_dict={x: data, keep_prob: 1.0})\r\nplt.imshow(y_value.reshape((28, 28)), cmap="magma", clim=(0, 1.0), origin='upper')\r\nplt.tick_params(labelbottom="off")\r\nplt.tick_params(labelleft="off")<\/pre>\n
\u4fee\u6b63\u5f8c\uff1a<\/p>\n
# Draw Input Data(x)\r\nplt.subplot(2*N_ROW, N_COL, 2*row*N_COL+col+1)\r\nplt.title('IN:%02d' % i)\r\nplt.imshow(data.reshape((28, 28)), cmap="magma", clim=(0, 1.0), origin='upper')\r\nplt.tick_params(labelbottom=False)\r\nplt.tick_params(labelleft=False)\r\n\r\n# Draw Output Data(y)\r\nplt.subplot(2*N_ROW, N_COL, 2*row*N_COL + N_COL+col+1)\r\nplt.title('OUT:%02d' % i)\r\ny_value = y.eval(session=sess, feed_dict={x: data, keep_prob: 1.0})\r\nplt.imshow(y_value.reshape((28, 28)), cmap="magma", clim=(0, 1.0), origin='upper')\r\nplt.tick_params(labelbottom=False)\r\nplt.tick_params(labelleft=False)<\/pre>\n
\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h4>\n
Matplotlib<\/strong><\/span>\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n
\uff081\uff09\u300cpip install matplotlib\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
AutoEncoder\u306e\u5b9f\u884c<\/h4>\n
AutoEncoder\u3092\u5b9f\u884c\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n
\uff081\uff09\u300cpython AutoEncoder.py\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
AutoEncoder\u306e\u5b9f\u884c\u304c\u7d42\u4e86\u3059\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u753b\u9762\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n
\"tens-ae03\"<\/p>\n
\u300cIN\uff1a00\u300d\u306e\u753b\u50cf\u3092AutoEncoder\u3092\u901a\u3059<\/strong><\/span>\u3068\u3001\u300cOUT\uff1a00\u300d\u306e\u753b\u50cf\u304c\u751f\u6210\u3055\u308c\u308b<\/strong><\/span>\u3068\u3044\u3046\u8868\u793a\u3067\u3059\u3002<\/p>\n
\u3061\u306a\u307f\u306b\u3001step\u6570\u30922000\u219220000\u306b\u5897\u3084\u3057\u305f\u7d50\u679c\u304c\u3001\u4ee5\u4e0b\u306e\u753b\u50cf\u3067\u3059\u3002<\/p>\n
\"tens-ae04\"<\/p>\n
\u6b8b\u5ff5\u306a\u304c\u3089\u3088\u304f\u8a00\u308f\u308c\u308b\u3053\u3068\u3067\u3059\u304c\u3001step\u6570\u3092\u5897\u3084\u3059\u3060\u3051\u3067\u306f\u3001\u3042\u307e\u308a\u5909\u5316\u306f\u3042\u308a\u307e\u305b\u3093\u306d\u3002<\/p>\n
\u300cH = 50\u300d\u306e\u6570\u5024\u3092\u5909\u3048\u308b\u3068\u3001\u5909\u5316\u304c\u308f\u304b\u308a\u3084\u3059\u3044\u3067\u3057\u3087\u3046\u3002<\/p>\n
Tensorflow\u3067AutoEncoder\u3092\u3084\u3063\u3066\u307f\u305f – Qiita<\/h3>\n
\"tens-ae05\"<\/p>\n
\u53c2\u8003\uff1ahttps:\/\/qiita.com\/onlyzs\/items\/12c675fb819b8da4ae85<\/a><\/p>\n
\u304d\u3085\u3046\u308a\u306e\u7570\u5e38\u691c\u51fa\uff08anomaly detection\uff09<\/strong><\/span>\u3092\u884c\u3046AutoEncoder\u3092\u4f5c\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n
\u30c7\u30fc\u30bf\u306e\u6e96\u5099<\/h4>\n
GitHub\u304b\u3089\u304d\u3085\u3046\u308a\u306e\u5199\u771f\u30c7\u30fc\u30bf\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u307e\u3059\u3002<\/p>\n
\uff081\uff09https:\/\/github.com\/workpiles\/CUCUMBER-9\/tree\/master\/prototype_1<\/a>\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3066\u3001\u300ccucumber-9-python.tar.gz\u300d<\/strong><\/span>\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u307e\u3059\u3002<\/p>\n
\uff082\uff09\u300ccucumber-9-python.tar.gz\u300d<\/strong><\/span>\u3092\u300cD:\\TensorFlow\\AutoEncoder2\\prototype_1\u300d<\/strong><\/span>\u30d5\u30a9\u30eb\u30c0\u306b\u3001\u89e3\u51cd\u3057\u307e\u3059\u3002<\/p>\n
\"tens-ae06\"<\/p>\n
\u30d7\u30ed\u30b0\u30e9\u30e0\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/h4>\n
\uff081\uff09https:\/\/github.com\/onlyzs89\/autoencoder\/tree\/master<\/a>\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3001\u300cClone or Download\u300d<\/strong><\/span>\u3092\u30af\u30ea\u30c3\u30af\u3057\u3066\u3001\u300cDownload ZIP\u300d<\/strong><\/span>\u3092\u30af\u30ea\u30c3\u30af\u3057\u307e\u3059\u3002<\/p>\n
\"tens-ae07\"<\/p>\n
\uff082\uff09\u300cautoencoder-master.zip\u300d<\/strong><\/span>\u3092\u300cD:\\TensorFlow\\AutoEncoder2\u300d<\/strong><\/span>\u30d5\u30a9\u30eb\u30c0\u306b\u3001\u89e3\u51cd\u3057\u307e\u3059\u3002<\/p>\n
\"tens-ae08\"<\/p>\n
\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h4>\n
OpenCV<\/strong><\/span>\u3001scipy<\/strong><\/span>\u3001scikit-learn<\/strong><\/span>\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n
\uff081\uff09\u300cpip install opencv-python\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
\uff082\uff09\u300cpip install scipy\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
\uff083\uff09\u300cpip install scikit-learn\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
AutoEncoder\u306e\u5b9f\u884c<\/h4>\n
\u6e96\u5099\u304c\u3067\u304d\u305f\u3089AutoEncoder\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n
\uff081\uff09\u300cpython training.py\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
AutoEncoder\u306e\u5b9f\u884c\u304c\u7d42\u4e86\u3059\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u753b\u9762\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n
\"tens-ae09\"<\/p>\n
\u4eca\u56de\u306e\u6b63\u89e3\u7387\u306f72%\u3067\u3057\u305f\u3002<\/strong><\/span><\/p>\n
TensorFlow\u3067Autoencoder\u3092\u5b9f\u88c5\u3057\u3066\u307f\u305f – Qiita<\/h3>\n
\"tens-ae10\"<\/p>\n
\u53c2\u8003\uff1ahttps:\/\/qiita.com\/TomokIshii\/items\/26b7414bdb3cd3052786<\/a><\/p>\n
MNIST\u30c7\u30fc\u30bf<\/strong><\/span>\u3092\u5727\u7e2e\u3001\u5fa9\u5143\u3059\u308bAutoEncoder\u3092\u4f5c\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n
\u30d7\u30ed\u30b0\u30e9\u30e0\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3068\u4fee\u6b63<\/h4>\n
https:\/\/gist.github.com\/tomokishii\/7ddde510edb1c4273438ba0663b26fc6<\/a>\u306b\u30a2\u30af\u30bb\u30b9\u3057\u3001\u300cDownload ZIP\u300d<\/strong><\/span>\u3092\u30af\u30ea\u30c3\u30af\u3057\u3001\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u305f\u30d5\u30a1\u30a4\u30eb\u3092\u300cD:\\TensorFlow\\AutoEncoder3\u300d<\/strong><\/span>\u306b\u89e3\u51cd\u3057\u307e\u3059\u3002<\/p>\n
\"tens-ae11\"<\/p>\n
\u3053\u306e\u5f8c\u306e\u624b\u9806\u3067\u300cmnist_ae1.py\u300d<\/strong><\/span>\u3092\u5b9f\u884c\u3057\u307e\u3059\u304c\u3001TensorFlow\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u30a2\u30c3\u30d7\u306b\u3068\u3082\u306a\u3044\u3001\u4e00\u90e8\u306e\u66f8\u304d\u304b\u305f\u3092\u5909\u66f4\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\uff081\uff09\u4fee\u6b63\u524d\uff1a<\/p>\n
# Train\r\ninit = tf.initialize_all_variables()<\/pre>\n
\u4fee\u6b63\u5f8c\uff1a<\/p>\n
# Train\r\ninit = tf.global_variables_initializer()<\/pre>\n
\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h4>\n
Matplotlib<\/strong><\/span>\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n
\uff081\uff09\u300cpip install matplotlib\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
AutoEncoder\u306e\u5b9f\u884c<\/h4>\n
MNIST\u30c7\u30fc\u30bf\u3092\u5727\u7e2e\u3001\u5fa9\u5143\u3059\u308bAutoEncoder\u306a\u306e\u3067\u3001\u5148\u306b\u8aac\u660e\u3057\u305f\u30e2\u30ce\u3068\u540c\u3058\u3060\u308d\u3046\u3068\u601d\u3044\u306a\u304c\u3089\u5b9f\u884c\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\uff081\uff09\u300cpython mnist_ae1.py\u300d<\/strong><\/span>\u3068\u5165\u529b\u3057\u3001Enter\u30ad\u30fc\u3092\u62bc\u3057\u307e\u3059\u3002<\/p>\n
mnist_ae1.png<\/strong><\/span>\u304c\u751f\u6210\u3055\u308c\u307e\u3059\u3002<\/p>\n
\"tens-ae12\"<\/p>\n
\u3053\u3061\u3089\u306f\u767d\u9ed2\u3067\u3059\u306d\u3002<\/p>\n
\u307e\u3068\u3081<\/h2>\n
\u4eca\u56de\u306f\u3001AutoEncoder\u30923\u3064\u5b9f\u884c\u3057\u3066\u307f\u307e\u3057\u305f\u3002<\/strong><\/span><\/p>\n
\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u8aad\u3093\u3067\u307f\u308b\u3068\u30011\u3064\u76ee\u306eAutoEncoder\u3067\u306f784\u6b21\u5143\u309250\u6b21\u5143\u306b\u524a\u6e1b<\/strong><\/span>\u30013\u3064\u76ee\u306eAutoEncoder\u3067\u306f784\u6b21\u5143\u3092625\u6b21\u5143\u306b\u524a\u6e1b<\/strong><\/span>\u3057\u3066\u304b\u3089\u306e\u5fa9\u5143\u3067\u3057\u305f\u3002<\/p>\n
\u6b21\u5143\u6570\u306f\u5927\u304d\u3044\u65b9\u304c\u3001\u5143\u306e\u753b\u50cf\u3092\u5fa9\u5143\u3057\u3084\u3059\u3044\u3068\u601d\u3046\u306e\u3067\u3059\u304c\u3001\u3069\u3061\u3089\u304b\u3068\u3044\u3046\u3068\u3001\u6b21\u5143\u6570\u304c\u5c0f\u3055\u30441\u3064\u76ee\u306eAutoEncoder\u306e\u307b\u3046\u304c\u5fa9\u5143\u3067\u304d\u3066\u3044\u308b<\/strong><\/span>\u3088\u3046\u306a\u6c17\u304c\u3057\u307e\u3059\u3002<\/p>\n
\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u6bd4\u8f03\u3057\u3066\u307f\u305f\u308a\u3001\u601d\u3046\u304c\u307e\u307e\u306b\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u5909\u3048\u3066\u3001\u3069\u306e\u3088\u3046\u306b\u5fa9\u5143\u7d50\u679c\u304c\u5909\u308f\u3063\u3066\u3044\u304f\u304b\u8abf\u3079\u3066\u307f\u305f\u308a\u3059\u308b\u306e\u3082\u3001\u3068\u3066\u3082\u9762\u767d\u3044\u306e\u3067\u304a\u52e7\u3081\u3067\u3059\u3002<\/strong><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
AutoEncoder\uff08\u30aa\u30fc\u30c8\u30a8\u30f3\u30b3\u30fc\u30c0\uff1a\u81ea\u5df1\u7b26\u53f7\u5316\u5668\uff09\u3092\u3054\u5b58\u77e5\u3067\u3057\u3087\u3046\u304b\uff1f AutoEncoder\u306f\u3001\u3068\u3066\u3082\u6709\u540d\u306a\u30e2\u30c7\u30eb\u3067\u3059\u304c\u3001TensorFlow\u306e\u516c\u5f0f\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306b\u306f\u3042\u308a\u307e\u305b\u3093\u3002 \u305d\u306e\u305f\u3081\u3001TensorFlow\u3092 […]<\/p>\n","protected":false},"author":16433,"featured_media":47062,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"swell_btn_cv_data":"","footnotes":""},"categories":[2350],"tags":[1071],"class_list":["post-47031","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python-study","tag-tensorflow"],"acf":[],"yoast_head":"\n\u3010TensorFlow\u3011\u516c\u5f0f\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306b\u306f\u306a\u3044AutoEncoder\u3092\u96c6\u3081\u3066\u307f\u305f | \u4f8d\u30a8\u30f3\u30b8\u30cb\u30a2\u30d6\u30ed\u30b0<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u8a18\u4e8b\u3067\u306f\u300c \u3010TensorFlow\u3011\u516c\u5f0f\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306b\u306f\u306a\u3044AutoEncoder\u3092\u96c6\u3081\u3066\u307f\u305f 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