爬取58同城 from bs4 import BeautifulSoupimport requestsurl = "https://qd.58.com/diannao/35200617992782x.shtml"web_data = requests.get(url)soup = BeautifulSoup(web_data.text, 'lxml')​title = soup.title.textcost = soup.select("div#basicinfo span.…

爬取我爱竞赛网的大量数据 首先获取每一种比赛信息的分类链接 def get_type_url(url):    web_data = requests.get(web_url)    soup = BeautifulSoup(web_data.text, 'lxml')    types = soup.select("#mn_P1_menu li a")    for type in types:        print(type.get_text())        get_num…

使用mongoDB 下载地址:https://www.mongodb.com/dr/fastdl.mongodb.org/win32/mongodb-win32-x86_64-2008plus-ssl-4.0.9.zip/download 百度链接:https://pan.baidu.com/s/1xhFsENTVvU-tnjK9ODJ7Ag 密码:ctyy mongoDB的安装 https://www.cnblogs.com/iamluoli/p/9254899.html 可视化Robo3T…

连续爬取多页数据 分析每一页url的关联找出联系 例如虎扑 第一页:https://voice.hupu.com/nba/1 第二页:https://voice.hupu.com/nba/2 第三页:https://voice.hupu.com/nba/3...... urls = ["https://voice.hupu.com/nba/{}".format(str(i)) for i in range(1, 30, 1)]print(urls) 这样就获得了30页的url ['ht…

用BeatuifulSoup和Requests爬取猫途鹰网 服务器与本地的交换机制 我们每次浏览网页都是再向网页所在的服务器发送一个Request,然后服务器接受到Request后返回Response给网页. Request 当前Http1.1版本共有get.post.head.put.options.connect.trace.delete共八种发送请求的方式.不过不需要全部记住,目前最常用的为get和post. Response 我们会在Response中得到服务器返回给我们的信息,例如st…

使用BeautifulSoup解析网页 Soup = BeautifulSoup(urlopen(html),'lxml') Soup为汤,html为食材,lxml为菜谱 from bs4 import BeautifulSoupfrom urllib.request import urlopenSoup = BeautifulSoup(urlopen("http://moumangtai.com/"), "lxml") 描述要爬取的东西在哪 选择要爬取的页面进行检…

Teaching Your Computer To Play Super Mario Bros. – A Fork of the Google DeepMind Atari Machine Learning Project Posted by ehrenbrav on August 25, 2016Leave a comment (14)Go to comments   For those who want to get right to the good stuff, the installa…

Machine and Deep Learning with Python Education Tutorials and courses Supervised learning superstitions cheat sheet Introduction to Deep Learning with Python How to implement a neural network How to build and run your first deep learning network Neur…

来自:CVPR 2014   作者:Yi Sun ,Xiaogang Wang,Xiaoao Tang 题目:Deep Learning Face Representation from Predicting 10,000 Classes 主要内容:通过深度学习来进行图像高级特征表示(DeepID),进而进行人脸的分类. 长处:在人脸验证上面做,能够非常好的扩展到其它的应用,而且夸数据库有效性:在数据库中的类别越多时,其泛化能力越强,特征比較少,不像其它特征好几K甚至上M,好的泛化能力+只是拟合…

Machine Learning for Developers Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learnin…