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4. 入力データ This is a pen. ↓ æ–‡å—コード化 [0x54, 0x68, 0x69, 0x73, 0x20, 0x69, 0x73,0x20, 0x61, 0x20, 0x70, 0x65, 0x6e, 0x2e] ・400æ–‡å—ã§æ–‡ç« を切ã£ã¦å…¥åŠ› 5. TensorFlow部分ã®ã‚³ãƒ¼ãƒ‰ x = tf.placeholder(tf.float32, [None, n_input_node]) W = tf.Variable(tf.zeros([n_input_node, 3])) b = tf.Variable(tf.zeros([3])) y = tf.nn.softmax(tf.matmul(x, W) + b) y_ = tf.placeholder(tf.float32, [None, 3]) cross_entropy = -tf.reduce_sum(y_*tf
Implementing a CNN for Text Classification in TensorFlow
The full code is available on Github. In this post we will implement a model similar to Kim Yoon’s Convolutional Neural Networks for Sentence Classification. The model presented in the paper achieves good classification performance across a range of text classification tasks (like Sentiment Analysis) and has since become a standard baseline for new text classification architectures. I’m assuming t
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Running your models in production with TensorFlow Serving
TensorFlow: ヘテãƒãªåˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ 上ã®å¤§è¦æ¨¡æ©Ÿæ¢°å¦ç¿’
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