本项目利用Python的scrapy框架爬取链家网的上海市租房信息，利用pandas、numpy、matplotlib、seaborn、folium
、wordcloud 等库进行数据分析和可视化，通过one-hot编码和文本特征提取出120个训练特征，搭建3层神经网络对上海市租房价格进行预测。
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This project uses Python s scratch framework to crawl the rental information of Shanghai from Lianjia Network. It uses databases such as Pandas, Numpy, Matplotlib, Seaborn, Folium, Wordcloud, etc. for data analysis and visualization. 120 training features are extracted through one hot encoding and text features, and a three-layer neural network is built to predict the rental price of Shanghai. (2020-12-10, Jupyter Notebook, 9753KB, 下载0次)