Уровень 0 · материалов: 3
В кластер входят документы, критикующие качество перевода конкретных технических книг или терминов на русский язык, и не входят тексты об общих математических ошибках авторов.
Общие признаки: ошибки в переводах, техническая литература, русскоязычные издания
Группа выше: Качество перевода технических текстов
Смысл: The main idea is to alert readers of the Russian translation of 'Mathematics for Machine Learning' about significant technical typos and translation errors in formulas and graphs that could hinder the learning process.
A detailed list of 22 critical mathematical and translation errors found in the Russian edition of M.P. Diezenroth's 'Mathematics for Machine Learning'.
Смысл: The text argues that the current Russian translation of 'Machine Learning' as 'Машинное обучение' (Machine Teaching/Learning) is conceptually flawed. The author advocates for using 'Машинное усвоение' (Machine Acquisition) to emphasize that the machine learns automatically through mathematical optimization, while humans merely provide data and training, not direct instruction.
The author argues that 'Machine Learning' should be translated as 'Machine Acquisition' to accurately reflect that machines automatically find patterns rather than being taught by humans.
Смысл: The text is a critical review of Robert Martin's book 'Clean Code,' arguing that while it contains valuable pragmatic advice on naming and function structure, it also suffers from dogmatism, internal inconsistencies regarding state/arguments, and a poor Russian translation.
A mixed review of 'Clean Code' that praises its practical tips on naming and testing but criticizes its dogmatism and poor Russian translation.