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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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Predictive Analytics Made Last Summer The Season Of Altcoins

Smart Data Collective

They found that predictive analytics algorithms were using social media data to forecast asset prices. But it’s clear they need help in choosing the best altcoins to buy from the more than 2000 high-risk cryptocurrencies available. This information can help forecast important price movements far more accurately than other sources.

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Humans and AI: Organizational Change

DataRobot

In 2000, Netflix offered Blockbuster a partnership, but the home movie provider turned it down. Participants viewed a graph of each song’s ranking from previous weeks and made a forecast for the coming week by entering a predicted placing from 1 to 100. Experts trusted their own judgment over the information offered to them.

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Machine learning-based Sell-In Forecasting for Consumer Electronics

bridgei2i

Machine learning-based Sell-In Forecasting for Consumer Electronics. With over 2000 products and a channel-focused Supply Chain planning approach, our Client wanted accurate Supply Chain Forecast for optimal product-availability within 8-week lead-times. Our Forecasting Engine is a Proven Tool to Improve Visibility.

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Cloud, SaaS boost Oracle sales, but competition exacts costs

CIO Business Intelligence

Despite the challenge of keeping up with the competition, Ellison sees increasing demand ahead, and forecasts accelerating uptake of Oracle cloud offerings. “Do Do I think this is a kind of a year 2000 like pandemic boom, people rushing to get to the cloud, and it’s going to slow down after?,” Ellison said.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Other techniques include simple re-sampling, where the minority class is continuously re-sampled until the number of obtained observations matches the size of the majority class, and focused under-sampling, where the discarded observations from the majority class are carefully selected to be away from the decision boundary (Japkowicz, 2000).

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insightsoftware Announces the Acquisition of Longview Solutions

Jet Global

Over 25,000 organizations worldwide rely on insightsoftware’s portfolio of best-in-class reporting, analytics, budgeting, forecasting, consolidation, and tax solutions to provide them with increased productivity, visibility, accuracy, and compliance. Visit insightsoftware.com for more information. About Longview. About Longview.

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