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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. So it should come as no surprise that Google has compiled and forecast time series for a long time.

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Climate change predictions: Anticipating and adapting to a warming world

IBM Big Data Hub

According to the Geophysical Fluid Dynamics Laboratory of the US’s National Oceanic and Atmospheric Association (NOAA), “Climate models reduce the uncertainty of climate change impacts, which aids in adaptation.” Global Change Research Program, 2017. Learn about the IBM Sustainability Accelerator. °C limit.

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6 ecommerce trends to watch

IBM Big Data Hub

Some forecasts suggest online retail might be responsible for half of all retail revenues by next year. Digital optimization and automation tools have made it cheaper and easier for businesses to use customer data or third-party data, creating intelligent ecommerce sites.

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Fitting Bayesian structural time series with the bsts R package

The Unofficial Google Data Science Blog

Forecasting (e.g. Time series data are having something of a moment in the tech blogs right now, with Facebook announcing their "Prophet" system for time series forecasting (Taylor and Letham 2017), and Google posting about its forecasting system in this blog (Tassone and Rohani 2017).