Unit 11 02.mp4 Hidden Markov Models.mp4YouTube↗  IA↗(long shot)
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Modelos ocultos de Markov, ou de forma abreviada HMMs [Hidden Markov Models],
Скрытые марковские модели, или сокращенно СММ (HMMs),
são utilizados para analisar ou prever séries temporais.
используются для анализа или предсказания последовательностей.
As aplicações incluem robótica, medicina, finanças,
Прикладное использование этих моделей можно увидеть в робототехнике, медицине, финансах,
tecnologias de fala e linguagem, e muitos e muitos outros domínios.
речевых и языковых технологиях, а также во многих других областях.
De fato, HMMs e filtros estão no núcleo de uma enorme quantidade de sistemas funcionando na prática,
Более того, СММ и фильтры лежат в основе огромного числа работающих на практике систем -
de elevadores até aviões.
от лифтов до самолетов.
Sempre que nos deparamos com uma série temporal que envolve ruído, sensores ou incerteza,
Каждый раз когда мы имеем дело с последовательностью, где есть помехи, или задействованы сенсоры, или существует неопределенность,
esse é o método a ser escolhido.
СММ - лучший способ обработки данных.
Hoje ensinarei sobre os HMMs e os filtros,
Поэтому сегодня я расскажу вам все об СММ и фильтрах,
para que você possa aplicar alguns algoritmos básicos em diversos problemas práticos.
чтобы вы смогли применять некоторые базовые алгоритмы для решения широкого спектра практических задач.
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