The project is an LSTM model written in PyTorch and trained on a small dataset of 3000 names (names.txt). Model generates names from model by selecting one out of top 3 letters suggested by model at a time until an EOS (End Of Sentence) character is not encountered.
Input for the model is any letter than you want the suggested names to start from.
Output are the 20 names generated by model.
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已经将项目的关键文件上传，包含微博爬虫、LDA主题分析和情感分析三个部分。 1.微博爬虫 实现微博评论爬取和微博用户信息爬取，一天大概十万条。 2.LDA主题分析 实现文档主题抽取，包括数据清洗及分词、主题数的确定（主题一致性和困惑度）和最优主题模型的选择（暴力搜索）。 3.情感分析 实现评论文本的
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