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import tensorflow as tf from sklearn.datasets import load_digits from sklearn.cross_validation import train_test_split from sklearn.preprocessing import LabelBinarizer #load data digits = load_digit... 阅读全文
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解释 compute_accuracy 的计算原理： 来自：https://blog.csdn.net/cy_tec/article/details/52046806 阅读全文
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import tensorflow as tf import numpy as np import matplotlib.pyplot as plt # # add layer # def add_layer(inputs, in_size, out_size,n_layer, activation_function = None): layer_name = '... 阅读全文
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注意：有些浏览器可能支持的不好，推荐使用最新的Chrome 命令行输入： tensorboard --logdir=logs/ 阅读全文
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import tensorflow as tf import numpy as np import matplotlib.pyplot as plt def add_layer(inputs, in_size, out_size, activation_function = None): Weights = tf.Variable(tf.random_normal([i... 阅读全文
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import tensorflow as tf import numpy as np def add_layer(inputs, in_size, out_size, activation_function = None): Weights = tf.Variable(tf.random_normal([in_size, out_size])) # hang lie ... 阅读全文
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import tensorflow as tf input1 = tf.placeholder(tf.float32) input2 = tf.placeholder(tf.float32) output = tf.multiply(input1, input2) with tf.Session() as sess: print(ses... 阅读全文
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加法 累加1 加3次 阅读全文
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import tensorflow as tf matrix1 = tf.constant([[3,3]]) # 1X2 matrix2 = tf.constant([[2], [2]]) product = tf.matmul(matrix1, matrix2) #method 1 #sess = tf.Ses... 阅读全文
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import tensorflow as tf import numpy as np # create data x_data = np.random.rand(100).astype(np.float32) y_data = x_data*0.1 + 0.3 ### create tensorflow structure start ### Weights ... 阅读全文