tensorflow构造第一个神经网络

coding:utf-8

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构造第一个神经网络模型
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构造神经网络结构

import tensorflow as tfimport numpy as npdef add_layer(inputs,in_size,out_size,activation_function=None):    Weights = tf.Variable(tf.random_normal([in_size,out_size],mean=0.0,stddev=1.0)) #标准正态分布    biases = tf.Variable(tf.zeros([1,out_size])+0.25)    out1 = tf.matmul(inputs,Weights)+biases    if activation_function is None:        outputs = out1    else:        outputs = activation_function(out1)    return outputs

构造数据

x_data = np.linspace(-1,1,500)[:,np.newaxis] noise = np.random.normal(0.1,0.05,x_data.shape)y_data = np.square(x_data)-0.25+noisexs = tf.placeholder(tf.float32,[None,1])ys = tf.placeholder(tf.float32,[None,1])l1 = add_layer(xs,1,10,activation_function = tf.nn.relu)y_prediction = add_layer(l1,10,1,activation_function=None)loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys-y_prediction),reduction_indices=[1]))train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)init = tf.initialize_all_variables()sess = tf.Session()sess.run(init)for i in range(2000):    sess.run(train_step,feed_dict={xs:x_data,ys:y_data})    if i %50:        print(sess.run(loss,feed_dict={xs:x_data,ys:y_data}))

结果：