{"type":"rich","url":"https://aipacommander.com/entry/2019/05/16/221930","provider_url":"https://hatena.blog","version":"1.0","height":"190","author_name":"aipacommander","author_url":"https://blog.hatena.ne.jp/aipacommander/","description":"\u30bf\u30a4\u30c8\u30eb\u306f\u3066\u304d\u3068\u30fc\u306b\u3064\u3051\u305f\u306e\u3067\u6b63\u3057\u304f\u306f\u306a\u3044 Colaboratory\u3067\u904a\u3093\u3067\u3044\u308b\u3068\u304d\u3001\u4ed6notebook\u3067\u4fdd\u5b58\u3057\u305f\u30e2\u30c7\u30eb\u3092\u8aad\u307f\u8fbc\u307f\u305f\u304b\u3063\u305f. import tensorflow as tf model = None # \u5b66\u7fd2\u6e08\u307f\u306e\u30e2\u30c7\u30eb\u3092\u60f3\u5b9a # Model is the full model w/o custom layers model.compile(optimizer=tf.keras.optimizers.Adam(), loss=tf.keras.losses.CategoricalCrossentropy(), metrics=['accuracy', tf.keras.metr\u2026","categories":["Python","Tensorflow"],"published":"2019-05-16 22:19:30","title":"Tensorflow2\u3067Keras\u307f\u305f\u3044\u306a\u4fdd\u5b58\u306e\u4ed5\u65b9\u3059\u308b\u3068\u6b7b\u306c","provider_name":"Hatena Blog","blog_url":"https://aipacommander.com/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Faipacommander.com%2Fentry%2F2019%2F05%2F16%2F221930\" title=\"Tensorflow2\u3067Keras\u307f\u305f\u3044\u306a\u4fdd\u5b58\u306e\u4ed5\u65b9\u3059\u308b\u3068\u6b7b\u306c - IT\u306e\u968a\u9577\u306e\u30d6\u30ed\u30b0\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","image_url":null,"blog_title":"IT\u306e\u968a\u9577\u306e\u30d6\u30ed\u30b0","width":"100%"}