Smart Data Collective
SEPTEMBER 7, 2021
Data-based insights can help make the right decisions, keep up with market trends and navigate the uncertainty. Setting the optimal prices. This global coffee brand has increased its revenue by 26% from 2016 to 2019. Big data is a not new concept, and it has been around for a while. However, this process can be automated.
CIO Business Intelligence
JUNE 28, 2023
These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As He points to cost savings from the reduction in laboratory tests, formulations, external software licenses, and the optimization of activities.
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The Unofficial Google Data Science Blog
APRIL 23, 2024
If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). Crucially, it takes into account the uncertainty inherent in our experiments.
IBM Big Data Hub
MARCH 8, 2024
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. a new living room couch—consumers can reduce uncertainty and the likelihood of returning a product by “trying it out” in their living room.
O'Reilly on Data
SEPTEMBER 11, 2019
So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. 2) is unchanged from Strata NY 2018, it’s up three places from Strata NY 2017—and eight places relative to 2016. What’s going on?
The Unofficial Google Data Science Blog
JULY 11, 2017
If both variances are positive then the optimal estimator of $y_{t+1}$ winds up being "exponential smoothing," where past data are forgotten at an exponential rate determined by the ratio of the two variances. Berge, Sinha, and Smolyansky (2016) also analyzed the data with the predictors at several lags.
The Unofficial Google Data Science Blog
MARCH 31, 2016
In the context of prediction problems, another benefit is that the models produce an estimate of the uncertainty in their predictions: the predictive posterior distribution. arXiv preprint arXiv:1602.00047, (2016). [8] These predictive posterior distributions have many uses such as in multi-armed bandit problems. bandit problems).
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