NOVA: Prediction by the Numbers Poster

NOVA: Prediction by the Numbers (2018)

2018-02-28 · EN
56%
Nutzerwertung
5 Stimmen
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Predictions underlie nearly every aspect of our lives, from sports, politics, and medical decisions to the morning commute. With the explosion of digital technology, the internet, and 'big data,' the science of forecasting is flourishing. But why do some predictions succeed spectacularly while others fail abysmally? And how can we find meaningful patterns amidst chaos and uncertainty? From the glitz of casinos and TV game shows to the life-and-death stakes of storm forecasts and the flaws of opinion polls that can swing an election, 'Prediction by the Numbers' explores stories of statistics in action. Yet advances in machine learning and big data models that increasingly rule our lives are also posing big, disturbing questions. How much should we trust predictions made by algorithms when we don't understand how they arrive at them? And how far ahead can we really forecast?

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Angezeigt wird USA. Verfügbarkeitsdaten von JustWatch.

Hauptbesetzung

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Jay O. SandersJay O. SandersNarrator (voice)Billy BaneBilly BaneActingGreg CarbinGreg CarbinActing

Movie DNA

Genre-AffinitätDokumentarfilmRegiepräferenz1028200Schauspielpräferenz1413944 · 1413945 · 65131LänderpräferenzUsEpochenpräferenz2010

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Predictions underlie nearly every aspect of our lives, from sports, politics, and medical decisions to the morning commute. With the explosion of digital technology, the internet, and 'big data,' the science of forecasting is flourishing. But why do some predictions succeed spectacularly while others fail abysmally? And how can we find meaningful patterns amidst chaos and uncertainty? From the glitz of casinos and TV game shows to the life-and-death stakes of storm forecasts and the flaws of opinion polls that can swing an election, 'Prediction by the Numbers' explores stories of statistics in action. Yet advances in machine learning and big data models that increasingly rule our lives are also posing big, disturbing questions. How much should we trust predictions made by algorithms when we don't understand how they arrive at them? And how far ahead can we really forecast?

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