<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[sinat_28852859的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/sinat_28852859</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; sinat_28852859]]></copyright><item><title><![CDATA[Tensorflow 图像识别分类]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82502996</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82502996</guid><author>sinat_28852859</author><pubDate>Fri, 07 Sep 2018 21:31:19 +0800</pubDate><description><![CDATA[dataset.py



import numpy as np
import os
import glob
from sklearn.utils import shuffle
import cv2

def load_train(train_path,img_size,classes):
    images=[]
    labels=[]
    img_names=[]
    cls=[...]]></description><category></category></item><item><title><![CDATA[tensorflow saver]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82468950</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82468950</guid><author>sinat_28852859</author><pubDate>Thu, 06 Sep 2018 21:53:58 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-
&quot;&quot;&quot;
Created on Thu Sep  6 21:22:31 2018

@author: lc
&quot;&quot;&quot;
import tensorflow as tf
import numpy as np

#save
#remember to define the same dtype and shape when restore

#W=tf.Vari...]]></description><category></category></item><item><title><![CDATA[tensorflow 卷积神经网络]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82468329</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82468329</guid><author>sinat_28852859</author><pubDate>Thu, 06 Sep 2018 21:10:12 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-
&quot;&quot;&quot;
Created on Thu Sep  6 16:12:22 2018

@author: lc
&quot;&quot;&quot;

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
# number 1 to 10 data
mnist=input_d...]]></description><category></category></item><item><title><![CDATA[Tensorflow drop_out]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82462556</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82462556</guid><author>sinat_28852859</author><pubDate>Thu, 06 Sep 2018 15:51:14 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-
&quot;&quot;&quot;
Created on Thu Sep  6 14:44:08 2018

@author: lc
&quot;&quot;&quot;

import tensorflow as tf
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
...]]></description><category></category></item><item><title><![CDATA[TensorFlow 分类栗子]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82430611</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82430611</guid><author>sinat_28852859</author><pubDate>Wed, 05 Sep 2018 20:55:59 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-
&quot;&quot;&quot;
Created on Wed Sep  5 19:53:23 2018

@author: lc
&quot;&quot;&quot;

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data

#如果没有这个数据集就下载，如果有就运行
mnist=input_d...]]></description><category></category></item><item><title><![CDATA[Tensorboard 2]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82427243</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82427243</guid><author>sinat_28852859</author><pubDate>Wed, 05 Sep 2018 17:12:38 +0800</pubDate><description><![CDATA[import tensorflow as tf
import matplotlib.pyplot as plt

def add_layer(inputs,in_size,out_size,n_layer,activation_function=None):
    layer_name='layer%s'%n_layer
    with tf.name_scope(layer_name):
 ...]]></description><category></category></item><item><title><![CDATA[Tensorboard]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82390895</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82390895</guid><author>sinat_28852859</author><pubDate>Tue, 04 Sep 2018 21:39:09 +0800</pubDate><description><![CDATA[import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt

def add_layer(inputs,in_size,out_size,activation_function=None):
    with tf.name_scope('layer'):
        with tf.name_scope...]]></description><category></category></item><item><title><![CDATA[tensorflow 神经网络]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82389553</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82389553</guid><author>sinat_28852859</author><pubDate>Tue, 04 Sep 2018 20:10:02 +0800</pubDate><description><![CDATA[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([in_size,out_size]...]]></description><category></category></item><item><title><![CDATA[tensorflow build a neural network]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82389283</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82389283</guid><author>sinat_28852859</author><pubDate>Tue, 04 Sep 2018 19:51:25 +0800</pubDate><description><![CDATA[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]))
    biases=tf.Variable(tf.zer...]]></description><category></category></item><item><title><![CDATA[tensorflow 激励函数]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82389264</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82389264</guid><author>sinat_28852859</author><pubDate>Tue, 04 Sep 2018 19:50:32 +0800</pubDate><description><![CDATA[当神经网络层数较少时，各种通用激励函数都行 
卷积神经网络：relu 
循环神经网络：relu 或tanh]]></description><category></category></item><item><title><![CDATA[Tensorflow  placeholder]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82381294</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82381294</guid><author>sinat_28852859</author><pubDate>Tue, 04 Sep 2018 11:49:49 +0800</pubDate><description><![CDATA[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(sess.run(output,feed_dict={input1:[7...]]></description><category></category></item><item><title><![CDATA[Tensorflow 变量与常量]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82381094</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82381094</guid><author>sinat_28852859</author><pubDate>Tue, 04 Sep 2018 11:38:10 +0800</pubDate><description><![CDATA[import tensorflow as tf
state=tf.Variable(0,name='counter')
#print(state.name)

one=tf.constant(1)
new_value=tf.add(state,one)
update=tf.assign(state,new_value)
#must have if have v
init=tf.initialize...]]></description><category></category></item><item><title><![CDATA[TensorFlow session 的两种打开关闭方式]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82355508</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82355508</guid><author>sinat_28852859</author><pubDate>Mon, 03 Sep 2018 21:41:48 +0800</pubDate><description><![CDATA[import tensorflow as tf
matrix1=tf.constant([[3,3]])
matrix2=tf.constant([[2],[2]])
product=tf.matmul(matrix1,matrix2)

##method1
#sess=tf.Session()
#result=sess.run(product)
#print(result)
#sess.clos...]]></description><category></category></item><item><title><![CDATA[tensorflow  小例子]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82355288</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82355288</guid><author>sinat_28852859</author><pubDate>Mon, 03 Sep 2018 21:28:03 +0800</pubDate><description><![CDATA[import tensorflow as tf
import numpy as np
x_data=np.random.rand(100).astype(np.float32)
y_data =x_data*0.1+0.3


#creat tensorflow start
Weights=tf.Variable(tf.random_uniform([1],-1.0,1.0))
biases=tf...]]></description><category></category></item><item><title><![CDATA[决策树、随机森林，小例子]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82119894</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82119894</guid><author>sinat_28852859</author><pubDate>Mon, 27 Aug 2018 22:04:06 +0800</pubDate><description><![CDATA[
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets.california_housing import fetch_california_housing
housing=fetch_california_housing()
print(housing.DESCR)
from sklearn impor...]]></description><category></category></item><item><title><![CDATA[第一篇，不知写啥，就贴代码吧。朴素贝叶斯，垃圾邮件检测。]]></title><link>https://blog.youkuaiyun.com/sinat_28852859/article/details/82084267</link><guid>https://blog.youkuaiyun.com/sinat_28852859/article/details/82084267</guid><author>sinat_28852859</author><pubDate>Sun, 26 Aug 2018 20:46:05 +0800</pubDate><description><![CDATA[from spam.spamEmail import spamEmailBayes
import re
#spam类对象
spam=spamEmailBayes()
#保存词频的词典
spamDict={}
normDict={}
testDict={}
#保存每封邮件中出现的词
wordsList=[]
wordsDict={}
#保存预测结果,key为文件名，值为预测类别
testResult...]]></description><category></category></item></channel></rss>