\[r(x)=p(x)-q(x)\]
週四（2月26日），香港法院以違反國家安全罪行為由，判處其父親郭賢生監禁八個月。這是首宗涉及海外被通緝社運人士家屬的國安案件判刑。，更多细节参见新收录的资料
쿠팡 김범석, 정보유출 99일만에 영어로 “사과”，详情可参考新收录的资料
2024年12月25日 星期三 新京报。新收录的资料对此有专业解读
But that’s unironically a good idea so I decided to try and do it anyways. With the use of agents, I am now developing rustlearn (extreme placeholder name), a Rust crate that implements not only the fast implementations of the standard machine learning algorithms such as logistic regression and k-means clustering, but also includes the fast implementations of the algorithms above: the same three step pipeline I describe above still works even with the more simple algorithms to beat scikit-learn’s implementations. This crate can therefore receive Python bindings and even expand to the Web/JavaScript and beyond. This also gives me the oppertunity to add quality-of-life features to resolve grievances I’ve had to work around as a data scientist, such as model serialization and native integration with pandas/polars DataFrames. I hope this use case is considered to be more practical and complex than making a ball physics terminal app.