{"width":"100%","provider_url":"https://hatena.blog","provider_name":"Hatena Blog","title":"Tensorboard\u3067\u53ef\u8996\u5316(2)","categories":["machine_learning"],"blog_url":"https://randommemory.hatenablog.com/","version":"1.0","height":"190","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Frandommemory.hatenablog.com%2Fentry%2F2019%2F09%2F16%2F015217\" title=\"Tensorboard\u3067\u53ef\u8996\u5316(2) - \u3089\u3093\u3060\u3080\u306a\u8a18\u61b6\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","description":"Udacity\u306eud187\u306eImage Classification with CNNs\u306e\u30cd\u30bf\u3092\u4f7f\u3063\u3066 model = tf.keras.Sequential([ tf.keras.layers.Conv2D(32, (3,3), padding='same', activation=tf.nn.relu, input_shape=(28, 28, 1)), tf.keras.layers.MaxPooling2D((2, 2), strides=2), tf.keras.layers.Conv2D(64, (3,3), padding='same', activation=tf.nn.rel\u2026","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/d/derwind/20190916/20190916015121.png","blog_title":"\u3089\u3093\u3060\u3080\u306a\u8a18\u61b6","author_name":"derwind","author_url":"https://blog.hatena.ne.jp/derwind/","published":"2019-09-16 01:52:17","url":"https://randommemory.hatenablog.com/entry/2019/09/16/015217","type":"rich"}