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机器学习面试知识点总结 | Hello World 💓
https://troublemeeter.github.io/ml-overview/
对面试中机器学习模型常碰到的问题进行总结对比。
常用句法分析工具包使用说明:Hanlp、StanfordNLP等 | Hello World 💓
https://troublemeeter.github.io/parser/
对比各个常用的自然语言处理工具包中的句法分析模块。
标签 | Hello World 💓
SQuAD2.0 刷榜top3模型分析 | Hello World 💓
https://troublemeeter.github.io/SQuAD2-0/
由于SQuAD2.0榜单一直在更新,所以top3模型也在更新。
GitHub Pages + Hexo + Next:博客搭建、功能设置及美化 | Hello World 💓
https://troublemeeter.github.io/next/
HexoHexo 是一个快速、简洁且高效的博客框架。Hexo 使用 Markdown(或其他渲染引擎)解析文章,在几秒内,即可利用靓丽的主题生成静态网页。 搭建博客框架搭建流程参照官网中文说明文档: https://hexo.io/zh-cn/docs/部署将搭建在本地的博客通过GitHub Pages部署在个人的GitHub中。从而能通过 <你的 GitHub 用户名>.github
介绍 | Hello World 💓
https://troublemeeter.github.io/about/
算法工程师,方向:自然语言处理 复旦研究生
常见机器学习分类模型Python实现 | Hello World 💓
https://troublemeeter.github.io/classification-models/
机器学习分类模型代码实现:KNN, LDA, NB, LR, CART, SVM, RF, XGBOOST, LightGBDT
MarkDown 使用细节 | Hello World 💓
https://troublemeeter.github.io/markdown/
记录使用遇到的一些常用的MarkDown命令
Transformer详解:各个特征维度分析推导 | Hello World 💓
https://troublemeeter.github.io/transformer/
谷歌在文章《Attention is all you need》中提出的transformer模型。如图主要架构:同样为encoder-decoder模式,左边部分是encoder,右边部分是decoder。TensorFlow代码:https://www.github.com/kyubyong/transformer
内容分类 | Hello World 💓
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