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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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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Modernize existing applications such as recommenders, search ranking, time series forecasting, etc. Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Use ML to unlock new data types—e.g., images, audio, video.

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PODCAST: Exploring Data, Digital and Artificial Intelligence through a Holistic Lens

bridgei2i

A Masters in Quantitative Economics from the Indian Statistical Institute (ISI), Calcutta, Prithvijit founded BRIDGEi2i in May 2011. Pritam Kanti Paul, CTO and Co-Founder of BRIDGEi2i Analytics, is a Gold Medalist in his batch of Masters in Statistics at the Indian Statistical Institute Calcutta.

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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 6: The Impact of COVID-19 on Supply Chain Management

bridgei2i

By allowing that, they could have a steady demand forecast based on sensing algorithms and react faster to such events. He has delivered hundreds of millions of dollars of impact to his clients in High-Tech CPG and Manufacturing Industries, particularly in the areas of demand forecasting, inventory and procurement planning. Transcript.

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4 Key Elements of Enterprise AI Strategy

bridgei2i

A Masters in Quantitative Economics from the Indian Statistical Institute (ISI), Calcutta, Prithvijit founded BRIDGEi2i in May 2011. Pritam Kanti Paul, CTO and Co-Founder of BRIDGEi2i Analytics, is a Gold Medalist in his batch of Masters in Statistics at the Indian Statistical Institute Calcutta.

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Time Series with R

Domino Data Lab

A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. For an illustration, we will make use of the World Bank API to download gross domestic product (GDP) for a number of countries from 1960 through 2011. > library(forecast). AICc=776.99

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Fitting Bayesian structural time series with the bsts R package

The Unofficial Google Data Science Blog

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. Forecasting (e.g. The other systems were written to do "forecasting at scale," a phrase that means something different in time series problems than in other corners of data science. by STEVEN L.