April 2025
Intermediate to advanced
624 pages
17h 41m
Portuguese (Portugal, Brazil)
Content preview from Deep Learning para programadores com fastai e PyTorch
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Capítulo 3. Ética dos dados
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Como discutimos nos Capítulos 1 e 2, por vezes os modelos de aprendizagem automática podem correr mal. Podem ter bugs. Podem ser confrontados com dados que nunca viram antes e comportar-se de formas inesperadas. Ou podem funcionar exatamente como foram concebidos, mas serem utilizados para algo que preferíamos que nunca tivessem sido utilizados.
Uma vez que a Deep Learning é uma ferramenta tão poderosa e pode ser utilizada para tantas coisas, torna-se particularmente importante que consideremos as consequências das nossas escolhas. O estudo filosófico da ética é oestudo do certo e do errado, incluindo a forma como podemos definir esses termos, reconhecer acções certas e erradas e compreender a ligação entre acções e consequências. O campo da ética dos dados existe hámuito tempo e muitos académicos dedicam-se a este campo. Está a ser utilizado para ajudar a definir políticas em muitas jurisdições; está a ser utilizado em empresas grandes e pequenas para considerar a melhor forma de garantir bons resultados ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.