Andrew White

MAY 4, 2020

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. As a result, Data, Analytics and AI are in even greater demand. The models are practically useless. This will give you a better chance of including the breadth of data to act as a base.

Uncertainty 90

Uncertainty Data Quality Consulting Predictive Modeling 90

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. A single model may also not shed light on the uncertainty range we actually face.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Sisense

SEPTEMBER 9, 2019

We were most interested in exploring if it was possible to predict the return rate on a new product based on historical return rates of products with similar features. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. It will be iterative.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. This may give a more accurate representation in the variability of predictions.

Risk 67

Risk ROI Modeling Metrics 67

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. These predictive posterior distributions have many uses such as in multi-armed bandit problems. bandit problems).

Modeling 40

Modeling Statistics Advertising Testing 40

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20