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.
儘管經歷了被關押的三個月,但劉亮認為,在扣留中心裡面,自己能夠得到比較人道的待遇,「他們會根據你的身體吃不同的飲食......一日三餐會根據不同營養的搭配,包括醫療,你只要跟officer(長官)報告,他們都能讓你即時就醫。」
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In Web streams, creating a simple producer/consumer pair requires TransformStream, manual encoding, and careful lock management: