April 2025
Intermediate to advanced
388 pages
12h 49m
Portuguese (Portugal, Brazil)
Content preview from Conceber sistemas de aprendizagem automática
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Capítulo 3. Fundamentos da engenharia de dados
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O aumento do ML nos últimos anos está intimamente ligado ao aumento dos grandes volumes de dados. Os grandes sistemas de dados, mesmo sem o AM, são complexos. Se não tiveres passado anos e anos a trabalhar com eles, é fácil perderes-te nos acrónimos. Há muitos desafios e possíveis soluções que estes sistemas geram. As normas da indústria, se é que existem, evoluem rapidamente à medida que surgem novas ferramentas e as necessidades da indústria se expandem, criando um ambiente dinâmico e em constante mudança. Se olhares para a pilha de dados de diferentes empresas de tecnologia, pode parecer que cada uma está a fazer o seu próprio trabalho.
Neste capítulo, abordaremos as noções básicas de engenharia de dados que, esperamos, te darão um pedaço de terra firme para te apoiares enquanto exploras a paisagem para as tuas próprias necessidades. Começaremos com as diferentes fontes de dados com que podes trabalhar num projeto típico de ML. Continuaremos a discutir os formatos em que os dados podem ser armazenados. O armazenamento de dados só é interessante se pretenderes recuperar esses dados mais tarde. Para recuperar os dados armazenados, é importante saber não apenas como eles estão formatados, mas também como estão estruturados. Os modelos de dados definem a forma como os dados armazenados num determinado formato de dados ...
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