The Unofficial Google Data Science Blog

APRIL 17, 2017

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.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

bridgei2i

MAY 26, 2020

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.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

The Unofficial Google Data Science Blog

JULY 11, 2017

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.

Forecasting 64

Forecasting Statistics Modeling Software 64

Occam's Razor

FEBRUARY 22, 2010

Feel better? : ) When should you start doing paid search advertising for tours to Italy for 2011? The secret to making optimal use of CI data lies in one single realization: You must ensure you understand how the data you are analyzing is collected. The Optimal Competitive Analysis Process. In May 2010 (!). use to your benefit.

Metrics 123

Metrics Advertising Reporting Software 123

Domino Data Lab

SEPTEMBER 25, 2019

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

Forecasting 87

Forecasting Modeling Statistics Optimization 87

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. If we were using CBOW, then a window size of 5 (for a total of 10 context words) could be near the optimal value. Note: Maas, A.,

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

MAY 21, 2019

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.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238