- Standford CS520, 完成第12课
- 阅读数量金融前三章
- 机器学习-白板推导系列, 完成线性回归与线性分类
- 重构量化预测代码
- 阅读Causal Inference Course Lectures前6节课
- 阅读因果推断入门1-9节
- 为了开发note网站, 学习vue.js
- 阅读facebookresearch/TaBERT源码, 绘制关系图
- 动感单车, 深蹲
- 继续阅读facebookresearch/TaBERT源码, 绘制关系图
- 继续vue.js
- 动感单车30min
- 学习vue.js, 接触到了phodal/phodit, 了解了travis ci, stencil, Electron, 感觉好无力, 要学习的好多, 技术路线好多
- 阅读facebookresearch/TaBERT源码, 绘制关系图
- 动感单车, 卷腹
- 重新阅读TABERT: Pretraining for Joint Understanding of Textual and Tabular Data, TAPAS: Weakly Supervised Table Parsing via Pre-training, Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
- 和USC的导师开会
- 动感单车30min
- 和USC的导师开会
- 调整作息
- 动感单车, 卷腹
- 重新阅读TABERT: Pretraining for Joint Understanding of Textual and Tabular Data, TAPAS: Weakly Supervised Table Parsing via Pre-training, Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
- 阅读npm相关资料, 尤其是How to use NPM (and import/export modules) in JavaScript, 完成了50%
- 重新阅读了TABERT: Pretraining for Joint Understanding of Textual and Tabular Data, TAPAS: Weakly Supervised Table Parsing via Pre-training
- 继续阅读facebookresearch/TaBERT源码
- 动感单车, 卷腹
- 重新阅读TAPAS: Weakly Supervised Table Parsing via Pre-training, Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
- 继续阅读facebookresearch/TaBERT源码
- 动感单车30min
- 继续阅读facebookresearch/TaBERT源码, 沿着主要逻辑基本读完了一遍
- 重新阅读TAPAS: Weakly Supervised Table Parsing via Pre-training, Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
- 继续阅读facebookresearch/TaBERT源码
- 动感单车30min
- 继续阅读facebookresearch/TaBERT源码
- 主要时间用来玩游戏了
- 继续阅读facebookresearch/TaBERT源码
- 和梁总开会讨论Semeval2021-task9
- 继续阅读facebookresearch/TaBERT源码
- 重新阅读TAPAS: Weakly Supervised Table Parsing via Pre-training, Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task