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学习《Tensorflow入门教程》记录  一、加载数据集 import numpy as np import tensorflow as tf import matplotlib.pyplot as plt from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_set...

学习《Tensorflow入门教程》记录  from tensorflow.examples.tutorials.mnist import input_data import tensorflow as tf mnist = input_data.read_data_sets('data/', one_hot=True) #读取数据集 #设置参数 numClasses = 10 #输出...

以Mnist数据集为例 一、神经网络结构  二、单层神经网络 import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("data/", one_hot=True) #设置参数 numClasses = 10 i...

学习《Tensorflow入门教程》记录  卷积神经网络流程框图如下： First Conv and Pool Layers ——Second Conv and Pool Layers——First Fully Connected Layer——Dropout Layer——Second Fully Connected Layer——Final Layer池化层简单理解：把卷积得到的结果进行降...

学习《Tensorflow入门教程》记录(1)矩阵乘法 # 创建一个变量 w = tf.Variable([[0.5,1.0]]) x = tf.Variable([[2.0],[1.0]]) y = tf.matmul(w, x) #全局变量初始化 init_op = tf.global_variables_initializer() with tf.Session() as s...

学习《Tensorflow入门教程》记录  import numpy as np import tensorflow as tf import matplotlib.pyplot as plt # 随机生成1000个点，围绕在y=0.1x+0.3的直线周围 num_points = 1000 vectors_set = [] for i in range(num_points): x...